grokking deep learning andrew w trask

Artificial Intelligence is the most exciting technology of the century, and Deep Learning is, quite literally, the ⠜brain⠝ behind the world⠙s smartest Artificial Intelligence systems out there. Grokking Deep Learning is the perfect place to begin the deep learning journey. Rather than just learning the ⠜black box⠝ API of some library or framework, readers will actually understand how to build these algorithms completely from scratch. Key Features:Build neural networks that can see and understand images Build an A.I. that will learn to defeat you in a classic Atari gameHands-on Learning Written for readers with high school-level math and intermediateprogramming skills. Experience with Calculus is helpful but notrequired. ABOUT THE TECHNOLOGY Deep Learning is a subset of Machine Learning, which is a field dedicated to the study and development of machines that can learn, often with the goal of eventually attaining general artificial intelligence.

Objev podobné jako Grokking Deep Learning - Andrew W Trask

Written for developers with some understanding of deep learning algorithms. Experience with reinforcement learning is not required. Grokking Deep Reinforcement Learning introduces this powerful machine learning approach, using examples, illustrations, exercises, and crystal-clear teaching. You ll love the perfectly paced teaching and the clever, engaging writing style as you dig into this awesome exploration of reinforcement learning fundamentals, effective deep learning techniques, and practical applications in this emerging field. We all learn through trial and error. We avoid the things that cause us to experience pain and failure. We embrace and build on the things that give us reward and success. This common pattern is the foundation of deep reinforcement learning: building machine learning systems that explore and learn based on the responses of the environment. â ¢ Foundational reinforcement learning concepts and methods â ¢ The most popular deep reinforcement learning agents solving high-dimensional environments â ¢ Cutting-edge agents that emulate human-like behavior and techniques for artificial general intelligence Deep reinforcement learning is a form of machine learning in which AI agents learn optimal behavior on their own from raw sensory input. The system perceives the environment, interprets the results of its past decisions and uses this information to optimize its behavior for maximum long-term return.

Objev podobné jako Grokking Deep Reinforcement Learning - Miguel Morales

It s time to dispel the myth that machine learning is difficult. Grokking Machine Learning teaches you how to apply ML to your projects using only standard Python code and high school-level math. No specialist knowledge is required to tackle the hands-on exercises using readily available machine learning tools! In Grokking Machine Learning, expert machine learning engineer Luis Serrano introduces the most valuable ML techniques and teaches you how to make them work for you. Practical examples illustrate each new concept to ensure you⠙re grokking as you go. You⠙ll build models for spam detection, language analysis, and image recognition as you lock in each carefully-selected skill. Packed with easy-to-follow Python-based exercises and mini-projects, this book sets you on the path to becoming a machine learning expert. Key Features · Different types of machine learning, including supervised and unsupervised learning · Algorithms for simplifying, classifying, and splitting data · Machine learning packages and tools · Hands-on exercises with fully-explained Python code samples For readers with intermediate programming knowledge in Python or a similar language. About the technology Machine learning is a collection of mathematically-based techniques and algorithms that enable computers to identify patterns and generate predictions from data. This revolutionary data analysis approach is behind everything from recommendation systems to self-driving cars, and is transforming industries from finance to art. Luis G. Serrano has worked as the Head of Content for Artificial Intelligence at Udacity and as a Machine Learning Engineer at Google, where he worked on the YouTube recommendations system. He holds a PhD in mathematics from the University of Michigan, a Bachelor and Masters from the University of Waterloo, and worked as a postdoctoral researcher at the University of Quebec at Montreal. He shares his machine learning expertise on a YouTube channel with over 2 million views and 35 thousand subscribers, and is a frequent speaker at artificial intelligence and data science conferences.

Objev podobné jako Grokking Machine Learning - Luis Serrano

The first edition of Deep Learning with Python is one of the best books on the subject. The second edition made it even better. - Todd Cook The bestseller revised! Deep Learning with Python, Second Edition is a comprehensive introduction to the field of deep learning using Python and the powerful Keras library. Written by Google AI researcher François Chollet, the creator of Keras, this revised edition has been updated with new chapters, new tools, and cutting-edge techniques drawn from the latest research. You ll build your understanding through practical examples and intuitive explanations that make the complexities of deep learning accessible and understandable. about the technologyMachine learning has made remarkable progress in recent years. We ve gone from near-unusable speech recognition, to near-human accuracy. From machines that couldn t beat a serious Go player, to defeating a world champion. Medical imaging diagnostics, weather forecasting, and natural language question answering have suddenly become tractable problems. Behind this progress is deep learning⠔a combination of engineering advances, best practices, and theory that enables a wealth of previously impossible smart applications across every industry sector about the bookDeep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. You ll learn directly from the creator of Keras, François Chollet, building your understanding through intuitive explanations and practical examples. Updated from the original bestseller with over 50% new content, this second edition includes new chapters, cutting-edge innovations, and coverage of the very latest deep learning tools. You ll explore challenging concepts and practice with applications in computer vision, natural-language processing, and generative models. By the time you finish, you ll have the knowledge and hands-on skills to apply deep learning in your own projects. what s insideDeep learning from first principlesImage-classification, imagine segmentation, and object detectionDeep learning for natural language processingTimeseries forecastingNeural style transfer, text generation, and image generation about the readerReaders need intermediate Python skills. No previous experience with Keras, TensorFlow, or machine learning is required. about the authorFrançois Chollet works on deep learning at Google in Mountain View, CA. He is the creator of the Keras deep-learning library, as well as a contributor to the TensorFlow machine-learning framework. He also does AI research, with a focus on abstraction and reasoning. His papers have been published at major conferences in the field, including the Conference on Computer Vision and Pattern Recognition (CVPR), the Conference and Workshop on Neural Information Processing Systems (NIPS), the International Conference on Learning Representations (ICLR), and others.

Objev podobné jako Deep Learning with Python - François Chollet

Engage the World Change the World Deep Learning has claimed the attention of educators and policymakers around the world. This book not only defines what deep learning is, but takes up the question of how to mobilize complex, whole-system change and transform learning for all students. Deep Learning is a global partnership that works to: transform the role of teachers to that of activators who design experiences that build global competencies using real-life problem solving; and supports schools, districts, and systems to shift practice and how to measure learning in authentic ways. This comprehensive strategy incorporates practical tools and processes to engage students, educators, and families in new partnerships and drive deep learning. Inside you⠙ll find: The Deep Learning Framework Vignettes and case studies from K-12 classrooms in 1,200 schools in seven countries Guidance for reaching disadvantaged and differently abled students Sample protocols and rubrics for assessment Videos demonstrating deep learning design and innovative leadership in practice Through learning partnerships, learning environments, new pedagogical practices, and leveraged digital skills, deep learning reaches students as never before ⠔ preparing them to be active, engaged participants in their future.

Objev podobné jako Deep Learning - Joanne Quinn, Michael Fullan, Joanne J. McEachen

Humans do a great job of reading text, identifying key ideas, summarizing, making connections, and other tasks that require comprehension and context. Recent advances in deep learning make it possible for computer systems to achieve similar results. Deep Learning for Natural Language Processing teaches you to apply deep learning methods to natural language processing (NLP) to interpret and use text effectively. In this insightful book, (NLP) expert Stephan Raaijmakers distills his extensive knowledge of the latest state-of-the-art developments in this rapidly emerging field. Key features An overview of NLP and deep learning â ¢ Models for textual similarity â ¢ Deep memory-based NLP â ¢ Semantic role labeling â ¢ Sequential NLP Audience For those with intermediate Python skills and general knowledge of NLP. No hands-on experience with Keras or deep learning toolkits is required. About the technology Natural language processing is the science of teaching computers to interpret and process human language. Recently, NLP technology has leapfrogged to exciting new levels with the application of deep learning, a form of neural network-based machine learning Stephan Raaijmakers is a senior scientist at TNO and holds a PhD in machine learning and text analytics. Heâ ™s the technical coordinator of two large European Union-funded research security-related projects. Heâ ™s currently anticipating an endowed professorship in deep learning and NLP at a major Dutch university.

Objev podobné jako Deep Learning for Natural Language Processing - Stephan Raaijmakers

If you ve been curious about artificial intelligence and machine learning but didn t know where to start, this is the book you ve been waiting for. Focusing on the subfield of machine learning known as deep learning, it explains core concepts and gives you the foundation you need to start building your own models. Rather than simply outlining recipes for using existing toolkits, Practical Deep Learning, 2nd Edition teaches you the why of deep learning and will inspire you to explore further. All you need is basic familiarity with computer programming and high school math - the book will cover the rest. After an introduction to Python, you ll move through key topics like how to build a good training dataset, work with the scikit-learn and Keras libraries, and evaluate your models performance. You ll also learn: How to use classic machine learning models like k-Nearest Neighbours, Random Forests, and Support Vector Machines, How neural networks work and how they re trained, How to use convolutional neural networks, How to develop a successful deep learning model from scratch. You ll conduct experiments along the way, building to a final case study that incorporates everything you ve learned. This second edition is thoroughly revised and updated, and adds six new chapters to further your exploration of deep learning from basic CNNs to more advanced models. New chapters cover fine tuning, transfer learning, object detection, semantic segmentation, multilabel classification, self-supervised learning, generative adversarial networks, and large language models. The perfect introduction to this dynamic, ever-expanding field, Practical Deep Learning, 2nd Edition will give you the skills and confidence to dive into your own machine learning projects.

Objev podobné jako Practical Deep Learning, 2nd Edition - Ronald T. Kneusel

Every other day we hear about new ways to put deep learning to good use: improved medical imaging, accurate credit card fraud detection, long range weather forecasting, and more. PyTorch puts these superpowers in your hands, providing a comfortable Python experience that gets you started quickly and then grows with you as you, and your deep learning skills, become more sophisticated. Deep Learning with PyTorch teaches you how to implement deep learning algorithms with Python and PyTorch. This book takes you into a fascinating case study: building an algorithm capable of detecting malignant lung tumors using CT scans. As the authors guide you through this real example, you ll discover just how effective and fun PyTorch can be. Key features â ¢ Using the PyTorch tensor API â ¢ Understanding automatic differentiation in PyTorch â ¢ Training deep neural networks â ¢ Monitoring training and visualizing results â ¢ Interoperability with NumPy Audience Written for developers with some knowledge of Python as well as basic linear algebra skills. Some understanding of deep learning will be helpful, however no experience with PyTorch or other deep learning frameworks is required. About the technology PyTorch is a machine learning framework with a strong focus on deep neural networks. Because it emphasizes GPU-based acceleration, PyTorch performs exceptionally well on readily-available hardware and scales easily to larger systems. Eli Stevens has worked in Silicon Valley for the past 15 years as a software engineer, and the past 7 years as Chief Technical Officer of a startup making medical device software. Luca Antiga is co-founder and CEO of an AI engineering company located in Bergamo, Italy, and a regular contributor to PyTorch.

Objev podobné jako Deep Learning with PyTorch - Eli Stevens, Luca Antiga

Humans learn best from feedbackâ ”we are encouraged to take actions that lead to positive results while deterred by decisions with negative consequences. This reinforcement process can be applied to computer programs allowing them to solve more complex problems that classical programming cannot. Deep Reinforcement Learning in Action teaches you the fundamental concepts and terminology of deep reinforcement learning, along with the practical skills and techniques youâ ™ll need to implement it into your own projects. Key features â ¢ Structuring problems as Markov Decision Processes â ¢ Popular algorithms such Deep Q-Networks, Policy Gradient method and Evolutionary Algorithms and the intuitions that drive them â ¢ Applying reinforcement learning algorithms to real-world problems Audience Youâ ™ll need intermediate Python skills and a basic understanding of deep learning. About the technology Deep reinforcement learning is a form of machine learning in which AI agents learn optimal behavior from their own raw sensory input. The system perceives the environment, interprets the results of its past decisions, and uses this information to optimize its behavior for maximum long-term return. Deep reinforcement learning famously contributed to the success of AlphaGo but thatâ ™s not all it can do! Alexander Zai is a Machine Learning Engineer at Amazon AI working on MXNet that powers a suite of AWS machine learning products. Brandon Brown is a Machine Learning and Data Analysis blogger at outlace.com committed to providing clear teaching on difficult topics for newcomers.

Objev podobné jako Deep Reinforcement Learning in Action - Alexander Zai, Brandon Brown

The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence.Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the field s key ideas and algorithms. This second edition has been significantly expanded and updated, presenting new topics and updating coverage of other topics.Like the first edition, this second edition focuses on core online learning algorithms, with the more mathematical material set off in shaded boxes. Part I covers as much of reinforcement learning as possible without going beyond the tabular case for which exact solutions can be found. Many algorithms presented in this part are new to the second edition, including UCB, Expected Sarsa, and Double Learning. Part II extends these ideas to function approximation, with new sections on such topics as artificial neural networks and the Fourier basis, and offers expanded treatment of off-policy learning and policy-gradient methods. Part III has new chapters on reinforcement learning s relationships to psychology and neuroscience, as well as an updated case-studies chapter including AlphaGo and AlphaGo Zero, Atari game playing, and IBM Watson s wagering strategy. The final chapter discusses the future societal impacts of reinforcement learning.

Objev podobné jako Reinforcement Learning - Andrew G. Barto, Richard S. Sutton

NVIDIA s Full-Color Guide to Deep Learning: All You Need to Get Started and Get Results To enable everyone to be part of this historic revolution requires the democratization of AI knowledge and resources. This book is timely and relevant towards accomplishing these lofty goals. -- From the foreword by Dr. Anima Anandkumar, Bren Professor, Caltech, and Director of ML Research, NVIDIA Ekman uses a learning technique that in our experience has proven pivotal to successâ ”asking the reader to think about using DL techniques in practice. His straightforward approach is refreshing, and he permits the reader to dream, just a bit, about where DL may yet take us. -- From the foreword by Dr. Craig Clawson, Director, NVIDIA Deep Learning Institute Deep learning (DL) is a key component of today s exciting advances in machine learning and artificial intelligence. Learning Deep Learning is a complete guide to DL. Illuminating both the core concepts and the hands-on programming techniques needed to succeed, this book is ideal for developers, data scientists, analysts, and others--including those with no prior machine learning or statistics experience.After introducing the essential building blocks of deep neural networks, such as artificial neurons and fully connected, convolutional, and recurrent layers, Magnus Ekman shows how to use them to build advanced architectures, including the Transformer. He describes how these concepts are used to build modern networks for computer vision and natural language processing (NLP), including Mask R-CNN, GPT, and BERT. And he explains how a natural language translator and a system generating natural language descriptions of images.Throughout, Ekman provides concise, well-annotated code examples using TensorFlow with Keras. Corresponding PyTorch examples are provided online, and the book thereby covers the two dominating Python libraries for DL used in industry and academia. He concludes with an introduction to neural architecture search (NAS), exploring important ethical issues and providing resources for further learning. Explore and master core concepts: perceptrons, gradient-based learning, sigmoid neurons, and back propagation See how DL frameworks make it easier to develop more complicated and useful neural networks Discover how convolutional neural networks (CNNs) revolutionize image classification and analysis Apply recurrent neural networks (RNNs) and long short-term memory (LSTM) to text and other variable-length sequences Master NLP with sequence-to-sequence networks and the Transformer architecture Build applications for natural language translation and image captioning NVIDIA s invention of the GPU sparked the PC gaming market. The company s pioneering work in accelerated computing--a supercharged form of computing at the intersection of computer graphics, high-performance computing, and AI--is reshaping trillion-dollar industries, such as transportation, healthcare, and manufacturing, and fueling the growth of many others.Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.

Objev podobné jako Learning Deep Learning - Magnus Ekman

The mathematical paradigms that underlie deep learning typically start out as hard-to-read academic papers, often leaving engineers in the dark about how their models actually function. Math and Architectures of Deep Learning bridges the gap between theory and practice, laying out the math of deep learning side by side with practical implementations in Python and PyTorch. Written by deep learning expert Krishnendu Chaudhury, you ll peer inside the ⠜black box⠝ to understand how your code is working, and learn to comprehend cutting-edge research you can turn into practical applications. about the technology It s important to understand how your deep learning models work, both so that you can maintain them efficiently and explain them to other stakeholders. Learning mathematical foundations and neural network architecture can be challenging, but the payoff is big. You ll be free from blind reliance on pre-packaged DL models and able to build, customize, and re-architect for your specific needs. And when things go wrong, you ll be glad you can quickly identify and fix problems. about the book Math and Architectures of Deep Learning sets out the foundations of DL in a way that s both useful and accessible to working practitioners. Each chapter explores a new fundamental DL concept or architectural pattern, explaining the underpinning mathematics and demonstrating how they work in practice with well-annotated Python code. You ll start with a primer of basic algebra, calculus, and statistics, working your way up to state-of-the-art DL paradigms taken from the latest research. By the time you re done, you ll have a combined theoretical insight and practical skills to identify and implement DL architecture for almost any real-world challenge.

Objev podobné jako Math and Architectures of Deep Learning - Krishnendu Chaudhury

Bridge the gap between modern machine learning and real-world biology with this practical, project-driven guide. Whether your background is in biology, software engineering, or data science, Deep Learning for Biology gives you the tools to develop deep learning models for tackling a wide range of biological problems.

Objev podobné jako Deep Learning for Biology - Charles Ravarani, Natasha Latysheva

Generative AI is the hottest topic in tech. This practical book teaches machine learning engineers and data scientists how to use TensorFlow and Keras to create impressive generative deep learning models from scratch

Objev podobné jako Generative Deep Learning - David Foster

Elektronická kniha - autor François Chollet, 328 stran, česky Strojové učení zaznamenalo v posledních letech pozoruhodný pokrok od téměř nepoužitelného rozpoznávání řeči a obrazu k nadlidské přesnosti. Od programů, které nedokázaly porazit jen trochu zkušenějšího hráče go, jsme dospěli k přemožiteli mistra světa. Za pokrokem ve vývoji učících se programů stojí tzv. hluboké učení (deep learning) ndash; kombinace technických vylepšení, osvědčených postupů a teorií, které umožnily vyvinout množství dříve nerealizovatelných inteligentních aplikací. S jejich pomocí pak můžeme například analyzovat text či mluvené slovo, překládat z jazyka do jazyka, rozpoznávat osoby na sociálních sítích nebo používat samořídící automobily. Tato kniha naučí čtenáře navrhovat hluboce se učící systémy v jazyku Python, který je v současnosti nejpoužívanějším programovacím jazykem pro vývoj těchto systémů, a knihovny Keras a TensorFlow používané většinou vítězů soutěží systémů pro...

Objev podobné jako Deep learning v jazyku Python (978-80-247-3100-1)

Strojové učení zaznamenalo v posledních letech pozoruhodný pokrok a dospělo od téměř nepoužitelného rozpoznávání řeči a obrazu k téměř nadlidské přesnosti, od programů, které nedokázaly porazit jen trochu zkušenějšího hráče šachu, až k přemožitelům mistrů světa.Za pokrokem ve vývoji učících se programů stojí tzv. hluboké učení (deep learning), což je kombinace teorií a osvědčených technických postupů, které umožnily vyvinout řadu dříve nerealizovatelných aplikací. S jejich pomocí můžeme analyzovat a syntetizovat text i mluvené slovo, překládat z jazyka do jazyka, rozpoznávat osoby nebo ovládat samořídící automobily.Kniha naučí čtenáře, jehož znalosti jazyka Python jsou na střední úrovni, navrhovat v tomto jazyku hluboce se učící systémy s pomocí knihoven Keras a TensorFlow, které používá většina autorů vítězných systémů ze soutěží v hlubokém učení. Výklad je založený na intuitivních vysvětleních a praktických příkladech. Náročné koncepty si procvičíte na aplikacích v oblasti počítačového vidění, zpracování přirozeného jazyka a generativních modelů. Získáte tak znalosti a praktické dovednosti, které vám umožní aplikovat hluboké učení ve vlastních projektech.Autorem knihy je François Chollet, tvůrce knihovny Keras a výzkumník v oblasti umělé inteligence společnosti Google. Výklad základních principů hlubokého učení i pokročilých dovedností Tvorba systému hlubokého učení pro počítačové vidění, časové řady, text i generování vlastních výtvorů (například obrázků) Způsob fungování moderních AI systémů typu ChatGPT Popis rozdílů při spouštění programů na CPU, GPU a FPU Práce s webovým prostředím Collaboration, které umožňuje používat GPU a FPU na serveru

Objev podobné jako Deep learning v jazyku Python - 2., rozšířené vydání - François Chollet

Help students move from surface-level learning to the transfer of understanding. How do social studies teachers maximize instruction to ensure students are prepared for an informed civic life? VISIBLE LEARNING® for Social Studies, Grades K-12 shows how the field is more than simply memorizing dates and factsâ ”it encapsulates the skillful ability to conduct investigations, analyze sources, place events in historical context, and synthesize divergent points of view. The Visible Learning framework demonstrates that learning is not an event, but rather a process in which students move from surface-level learning to deep learning, and then onto the transfer of concepts, skills, and strategies. Encouraging learners to explore different facets of society, history, geography, and more, best practices for applying visible learning to social studies curriculum are presented through: ·        A scaffolded approach, including surface-level learning, deep learning, and transfer of learning ·        Examples of strategies, lessons, and activities best suited for each level of learning ·        Planning tools, rubrics, and templates to guide instruction Teachers must understand the impact they have on students and select approaches to maximize that impact. This book will guide you through the process of identifying the right strategy for the right time to successfully move students through surface, deep, and transfer learning. Â

Objev podobné jako Visible Learning for Social Studies, Grades K-12 - Julie Stern, John Hattie, Douglas Fisher, Nancy Frey

Selected as the Michigan Council of Teachers of Mathematics winter book club book! Rich tasks, collaborative work, number talks, problem-based learning, direct instruction⠦with so many possible approaches, how do we know which ones work the best? In Visible Learning for Mathematics, six acclaimed educators assert it⠙s not about which one⠔it⠙s about when⠔and show you how to design high-impact instruction so all students demonstrate more than a year⠙s worth of mathematics learning for a year spent in school. That⠙s a high bar, but with the amazing K-12 framework here, you choose the right approach at the right time, depending upon where learners are within three phases of learning: surface, deep, and transfer. This results in visible learning because the effect is tangible. The framework is forged out of current research in mathematics combined with John Hattie⠙s synthesis of more than 15 years of education research involving 300 million students. Chapter by chapter, and equipped with video clips, planning tools, rubrics, and templates, you get the inside track on which instructional strategies to use at each phase of the learning cycle: Surface learning phase: When⠔through carefully constructed experiences⠔students explore new concepts and make connections to procedural skills and vocabulary that give shape to developing conceptual understandings. Deep learning phase: When⠔through the solving of rich high-cognitive tasks and rigorous discussion⠔students make connections among conceptual ideas, form mathematical generalizations, and apply and practice procedural skills with fluency. Transfer phase: When students can independently think through more complex mathematics, and can plan, investigate, and elaborate as they apply what they know to new mathematical situations. To equip students for higher-level mathematics learning, we have to be clear about where students are, where they need to go, and what it looks like when they get there. Visible Learning for Math brings about powerful, precision teaching for K-12 through intentionally designed guided, collaborative, and independent learning.

Objev podobné jako Visible Learning for Mathematics, Grades K-12 - Douglas Fisher, Nancy Frey, John Hattie, Sara Delano Moore, Linda M. Gojak, William Mellman

Develop a mathematical intuition around machine learning algorithms to improve model performance and effectively troubleshoot complex ML problems. For intermediate machine learning practitioners familiar with linear algebra, probability, and basic calculus. Machine Learning Algorithms in Depth dives into the design and underlying principles of some of the most exciting machine learning (ML) algorithms in the world today. With a particular emphasis on probability-based algorithms, you will learn the fundamentals of Bayesian inference and deep learning. You will also explore the core data structures and algorithmic paradigms for machine learning. You will explore practical implementations of dozens of ML algorithms, including: Monte Carlo Stock Price Simulation Image Denoising using Mean-Field Variational Inference EM algorithm for Hidden Markov Models Imbalanced Learning, Active Learning and Ensemble Learning Bayesian Optimisation for Hyperparameter Tuning Dirichlet Process K-Means for Clustering Applications Stock Clusters based on Inverse Covariance Estimation Energy Minimisation using Simulated Annealing Image Search based on ResNet Convolutional Neural Network Anomaly Detection in Time-Series using Variational Autoencoders Each algorithm is fully explored with both math and practical implementations so you can see how they work and put into action. About the technology Fully understanding how machine learning algorithms function is essential for any serious ML engineer. This vital knowledge lets you modify algorithms to your specific needs, understand the trade-offs when picking an algorithm for a project, and better interpret and explain your results to your stakeholders. This unique guide will take you from relying on one-size-fits-all ML libraries to developing your own algorithms to solve your business needs.

Objev podobné jako Machine Learning Algorithms in Depth - Vadim Smolyakov

An advanced book for researchers and graduate students working in machine learning and statistics who want to learn about deep learning, Bayesian inference, generative models, and decision making under uncertainty.An advanced counterpart to Probabilistic Machine Learning: An Introduction, this high-level textbook provides researchers and graduate students detailed coverage of cutting-edge topics in machine learning, including deep generative modeling, graphical models, Bayesian inference, reinforcement learning, and causality. This volume puts deep learning into a larger statistical context and unifies approaches based on deep learning with ones based on probabilistic modeling and inference. With contributions from top scientists and domain experts from places such as Google, DeepMind, Amazon, Purdue University, NYU, and the University of Washington, this rigorous book is essential to understanding the vital issues in machine learning.Covers generation of high dimensional outputs, such as images, text, and graphs Discusses methods for discovering insights about data, based on latent variable models Considers training and testing under different distributionsExplores how to use probabilistic models and inference for causal inference and decision makingFeatures online Python code accompanimentÂ

Objev podobné jako Probabilistic Machine Learning - Kevin P. Murphy

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform.Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.This Second Edition features new chapters on deep learning, survival analysis, and multiple testing, as well as expanded treatments of naïve Bayes, generalized linear models, Bayesian additive regression trees, and matrix completion. R code has been updated throughout to ensure compatibility.

Objev podobné jako An Introduction to Statistical Learning - Trevor Hastie, Robert Tibshirani, Daniela Witten, Gareth James

MACHINE LEARNING FOR BUSINESS ANALYTICS Machine learning â ”also known as data mining or data analyticsâ ” is a fundamental part of data science. It is used by organizations in a wide variety of arenas to turn raw data into actionable information. Machine Learning for Business Analytics: Concepts, Techniques, and Applications in R provides a comprehensive introduction and an overview of this methodology. This best-selling textbook covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, rule mining, recommendations, clustering, text mining, experimentation, and network analytics. Along with hands-on exercises and real-life case studies, it also discusses managerial and ethical issues for responsible use of machine learning techniques. This is the second R edition of Machine Learning for Business Analytics. This edition also includes: A new co-author, Peter Gedeck, who brings over 20 years of experience in machine learning using RAn expanded chapter focused on discussion of deep learning techniquesA new chapter on experimental feedback techniques including A/B testing, uplift modeling, and reinforcement learningA new chapter on responsible data scienceUpdates and new material based on feedback from instructors teaching MBA, Masters in Business Analytics and related programs, undergraduate, diploma and executive courses, and from their studentsA full chapter devoted to relevant case studies with more than a dozen cases demonstrating applications for the machine learning techniquesEnd-of-chapter exercises that help readers gauge and expand their comprehension and competency of the material presentedA companion website with more than two dozen data sets, and instructor materials including exercise solutions, slides, and case solutions This textbook is an ideal resource for upper-level undergraduate and graduate level courses in data science, predictive analytics, and business analytics. It is also an excellent reference for analysts, researchers, and data science practitioners working with quantitative data in management, finance, marketing, operations management, information systems, computer science, and information technology.

Objev podobné jako Machine Learning for Business Analytics - Peter Gedeck, Galit Shmueli, Peter C. Bruce, Nitin R. Patel, Inbal Yahav

The first comprehensive introduction to Multi-Agent Reinforcement Learning (MARL), covering MARLÂ’s models, solution concepts, algorithmic ideas, technical challenges, and modern approaches.Multi-Agent Reinforcement Learning (MARL), an area of machine learning in which a collective of agents learn to optimally interact in a shared environment, boasts a growing array of applications in modern life, from autonomous driving and multi-robot factories to automated trading and energy network management. This text provides a lucid and rigorous introduction to the models, solution concepts, algorithmic ideas, technical challenges, and modern approaches in MARL. The book first introduces the fieldÂ’s foundations, including basics of reinforcement learning theory and algorithms, interactive game models, different solution concepts for games, and the algorithmic ideas underpinning MARL research. It then details contemporary MARL algorithms which leverage deep learning techniques, covering ideas such as centralized training with decentralized execution, value decomposition, parameter sharing, and self-play. The book comes with its own MARL codebase written in Python, containing implementations of MARL algorithms that are self-contained and easy to read. Technical content is explained in easy-to-understand language and illustrated with extensive examples, illuminating MARL for newcomers while offering high-level insights for more advanced readers. First textbook to introduce the foundations and applications of MARL, written by experts in the fieldIntegrates reinforcement learning, deep learning, and game theoryPractical focus covers considerations for running experiments and describes environments for testing MARL algorithmsExplains complex concepts in clear and simple languageClassroom-tested, accessible approach suitable for graduate students and professionals across computer science, artificial intelligence, and robotics Resources include code and slidesÂ

Objev podobné jako Multi-Agent Reinforcement Learning - Filippos Christianos, Stefano V. Albrecht

A Le Creuset Classic 21 cm magas, Deep Teal színű borsómalom beállítható keramikus őrlő mechanikával rendelkezik. Az ABS műanyagból készült, strapabíró kivitelű termék nagy űrtartalmú tartállyal és ergonomikus formatervezéssel készült. Elegáns megjelenése dekoratív konyhai kiegészítővé teszi.

• Beállítható keramikus őrlő mechanika finom vagy durva őrléshez
• Erős ABS műanyag konstrukció és nagy űrtartalmú tartály
• Ergonomikus design kényelmes kezeléshez
• Elegáns Deep Teal szín, amely dekoratív elem a konyhában

Objev podobné jako Mlýnek na pepř CLASSIC 21 cm, DEEP TEAL, plast, Le Creuset

A 28 cm átmérőjű Le Creuset kamenina tortaforma a Deep Teal színben készült. A forma kiválóan alkalmas torták, piték és quiche-k sütésére, egyenletes hőelosztást biztosít. Hosszú távú hőtartása, könnyű tisztíthatósága és esztétikus megjelenése mindennapi és ünnepi használatra egyaránt ideális.

• Kiváló minőségű kameninából készült, amely egyenletes hőelosztást és tökéletes sütési eredményt biztosít.
• Hullámos széle professzionális megjelenést kölcsönöz a süteményeknek, ideális ünnepi alkalmakra.
• Széles hőmérsékleti toleranciája (-23°C-tól +260°C-ig) lehetővé teszi a sütőben, mikróban, fagyasztóban való használatot és mosogatógépben való tisztítást.
• A mély türkiz (Deep Teal) szín és a luxus megjelenés bármely konyhát vagy asztaldíszítést felemel.

Objev podobné jako Forma na koláč 28 cm, DEEP TEAL, kamenina, Le Creuset

A Le Creuset Signature 30 cm-es, 3,5 literes öntöttvas kastrol Deep Teal színben készült. Az edény tökéletes hőeloszlást és tartást biztosít, ideális serpenyőzéshez, pároláshoz, sütéshez és főzéshez. Minden típusú főzőlappal kompatibilis, beleértve az indukciósat, és élettartamra szóló garanciával rendelkezik.

• Kiváló hőeloszlású és hőtartó öntöttvas kivitel
• Többfunkciós használat: serpenyőzés, párolás, sütés, főzés
• Minden típusú főzőlapra alkalmas, beleértve az indukciósat is
• Élettartamra szóló garancia és prémium minőség

Objev podobné jako Kastrol SIGNATURE 30 cm, 3,5 l, DEEP TEAL, litina, Le Creuset

A Le Creuset Classic 21 cm-es kézi sómalom mély türkiz színben készült, állítható kerámia őrlőmechanizmussal és tartós ABS műanyag kivitelben. Mindennapi főzéshez és asztali tálaláshoz egyaránt alkalmas, különböző típusú sók őrlésére. Kiváló minőségű anyagokból készült, mely biztosítja a hosszú élettartamot és megbízható működést.

• Állítható kerámia őrlőmechanizmus korrózióálló anyagból
• Robusztus ABS műanyag kivitel hosszú élettartammal
• Elegáns mély türkiz szín és modern design
• Könnyű töltés és egyszerű őrlésfinomság-beállítás

Objev podobné jako Mlýnek na sůl CLASSIC 21 cm, DEEP TEAL, plast, Le Creuset

A Le Creuset Deep Teal színű só- és borsóróló készlet két 11 cm magas műanyag eszközből áll. Kerámia őrlőmechanizmusa alkalmas só és bors őrlésére, állítható finomsági fokozattal. A készlet kompakt méretű, tartós kivitelű és ajándékdobozban kapható.

• Kerámia őrlőmechanizmus sóra és borsra egyaránt
• Kompakt 11 cm-es méret könnyű tároláshoz
• Állítható őrlési fokozat S és P jelöléssel
• Erős ABS műanyag test tartós színállósággal

Objev podobné jako Sada mlýnků na sůl a pepř 11 cm, sada 2 ks, DEEP TEAL, plast, Le Creuset

Ez a 10 cm átmérőjű, 250 ml-es Le Creuset kőedény egy kompakt, sokoldalú konyhai eszköz. A kőedény anyag kiváló hőtartást és egyenletes hőelosztást biztosít, miközben sütőben, mikróban és mosogatógépben is biztonságosan használható. Kiválóan alkalmas egyedi adagok sütésére, melegítésére és elegáns asztali tálalására.

• Kiváló hőelosztású, tartós kőedény anyag
• Többfunkciós: sütő, mikró, mosogatógép biztonságos
• Elegáns Deep Teal szín és ikonikus design
• Ideális egy adagos ételek, mártások, előételek készítéséhez és tálalásához

Objev podobné jako Zapékací mísa 10 cm, 250 ml, DEEP TEAL, kamenina, Le Creuset

A Le Creuset Coupe 22 cm átmérőjű, 960 ml-es étkező tál kameninából készült, Deep Teal színben. A tál sütőben, mikrohullámú sütőben és mosogatógépben is használható, -23°C-tól +260°C-ig terjedő hőmérséklet-tartományban. Mély kialakítása ideális tésztás ételek és egy adagos fogások tálalásához.

• 22 cm átmérőjű, 960 ml-es mély tál ideális tésztáshoz és egy adagos ételekhez
• Sütőben, mikrohullámú sütőben és grill alatt is biztonságosan használható (-23°C-tól +260°C-ig)
• Karcálló, könnyen tisztítható kamenina anyag, mosogatógépben is mosható
• Modern Deep Teal szín és organikus forma, amely kiemeli az étel színeit és textúráit

Objev podobné jako Jídelní mísa COUPE 22 cm, 960 ml, DEEP TEAL, kamenina, Le Creuset

A Le Creuset HERITAGE 19 cm-es, 1,1 literes sütőedény kőedényből készült, mely -23°C és +260°C közötti hőmérsékletet is kibír. Egyenes fogantyúi biztonságos fogást biztosítanak, és könnyen tisztítható. Az edény sütőben, mikrohullámú sütőben, fagyasztóban és grill alatt is használható.

• -23°C és +260°C közötti hőállóság (mikrohullámú, sütő, fagyasztó, grill)
• könnyen tisztítható, nem szívja fel a szagokat
• könnyen megfogható, egyenes fogantyúk
• egyenletes hőeloszlású kőedény anyag

Objev podobné jako Zapékací mísa HERITAGE 19 cm, 1,1 l, DEEP TEAL, kamenina, Le Creuset

A Le Creuset HERITAGE 32 cm-es, 4 literes kőedény sütőtál Deep Teal színben. Nagy kapacitású, ideális lasagne, rakott ételek, sült zöldségek és desszertek készítéséhez. Hőálló anyaga biztosítja az egyenletes hőeloszlást, és közvetlenül a sütőből tálalható asztalra.

• 4 literes kapacitás, ideális családi főzéshez és vendégséghez
• Kiváló hőeloszlású kőedény, -23°C-tól +260°C-ig hőálló
• Könnyen tisztítható, karcolásálló bevonattal, mosogatógépbiztos
• Ergonomikus, barázdált fogantyúk biztonságos fogáshoz

Objev podobné jako Zapékací mísa HERITAGE 32 cm, 4 l, DEEP TEAL, kamenina, Le Creuset

A Le Creuset Coupe 16 cm átmérőjű, 770 ml-es kőedény tál Deep Teal színben. A tál hőálló -20 °C-tól +260 °C-ig, sütőben, mikróban és mosogatógépben is használható. A kőedény anyag tartós, karcolásálló, és kiváló hőtartó képességgel rendelkezik.

• Kiváló hőtartó képesség -20 °C-tól +260 °C-ig
• Tartós, karcolásálló kőedény felület, könnyű tisztítás
• Univerzális használat: sütő, mikró, grill, mosogatógép
• Minimalista design, kényelmes forma, stabil asztali állás

Objev podobné jako Jídelní miska COUPE 16 cm, 770 ml, DEEP TEAL, kamenina, Le Creuset

Distributed across servers, difficult to test, and resistant to modificationâ ”modern software is complex. Grokking Simplicity is a friendly, practical guide that will change the way you approach software design and development. It introduces a unique approach to functional programming that explains why certain features of software are prone to complexity, and teaches you the functional techniques you can use to simplify these systems so that theyâ ™re easier to test and debug. Available in PDF (ePub, kindle, and liveBook formats coming soon). about the technologyEven experienced developers struggle with software systems that sprawl across distributed servers and APIs, are filled with redundant code, and are difficult to reliably test and modify. Adopting ways of thinking derived from functional programming can help you design and refactor your codebase in ways that reduce complexity, rather than encouraging it. Grokking Simplicity lays out how to use functional programming in a professional environment to write a codebase thatâ ™s easier to test and reuse, has fewer bugs, and is better at handling the asynchronous nature of distributed systems. about the bookIn Grokking Simplicity, youâ ™ll learn techniques and, more importantly, a mindset that will help you tackle common problems that arise when software gets complex. Veteran functional programmer Eric Normand guides you to a crystal-clear understanding of why certain features of modern software are so prone to complexity and introduces you to the functional techniques you can use to simplify these systems so that theyâ ™re easier to read, test, and debug. Through hands-on examples, exercises, and numerous self-assessments, youâ ™ll learn to organize your code for maximum reusability and internalize methods to keep unwanted complexity out of your codebase. Regardless of the language youâ ™re using, the ways of thinking in this book will help recognize problematic code and tame even the most complex software. what s inside Apply functional programming principles to reduce codebase complexity Work with data transformation pipelines for code thatâ ™s easier to test and reuse Tools for modeling time to simplify asynchrony 60 exercises and 100 questions to test your knowledge about the readerFor experienced programmers. Examples are in JavaScript. about the author Eric Normand has been a functional programmer since 2001 and has been teaching functional programming online and in person since 2007. Visit LispCast.com to see more of his credentials.

Objev podobné jako Grokking Simplicity - Eric Normand

A friendly, fully-illustrated introduction to the most important computer programming algorithms. The algorithms you ll use most often as a programmer have already been discovered, tested, and proven. This book will prepare you for those pesky algorithms questions in every programming job interview and help you apply them in your day-to-day work. And if you want to understand them without slogging through dense multipage proofs, this is the book for you. In Grokking Algorithms, Second Edition you will discover: Search, sort, and graph algorithms Data structures such as arrays, lists, hash tables, trees, and graphs NP complete and greedy algorithms Performance trade-offs between algorithms Exercises and code samples in every chapter Over 400 illustrations with detailed walkthroughs The first edition of Grokking Algorithms proved to over 100,000 readers that learning algorithms doesn t have to be complicated or boring! This new edition now includes fresh coverage of trees, NP complete problems, and code updates to Python 3. With easy-to-read, friendly explanations, clever examples, and exercises to sharpen your skills as you learn, youâ ™ll actually enjoy learning these important algorithms.

Objev podobné jako Grokking Algorithms - Aditya Bhargava

AI is primed to revolutionize the way we build applications, offering exciting new ways to solve problems, uncover insights, innovate new products, and provide better user experiences. Successful AI is based on a set of core algorithms that form a base of knowledge shared by all data scientists. Grokking Artificial Intelligence Algorithms is a fully-illustrated and interactive tutorial guide to the different approaches and algorithms that underpin AI. Written in simple language and with lots of visual references and hands-on examples, readers learn the concepts, terminology, and theory they need to effectively incorporate AI algorithms into their applications. Grokking Artificial Intelligence Algorithms uses simple language, jargon-busting explanations, and hand-drawn diagrams to open up complex algorithms. Donâ ™t worry if you arenâ ™t a calculus wunderkind; youâ ™ll need only the algebra you picked up in math class. â ¢ Use cases for different AI algorithms â ¢ How to encode problems and solutions using data structures â ¢ Intelligent search for game playing â ¢ Ant colony algorithms for path finding â ¢ Evolutionary algorithms for optimization problems For software developers with high school-level algebra and calculus skills.

Objev podobné jako Grokking Artificial Intelligence Algorithms - Rishal Hurbans

Reacher had no idea where he was. No idea how he had got there. But someone must have brought him.And shackled him. And whoever had done those things was going to rue the day. That was for damn sure.Jack Reacher wakes up, alone, in the dark, handcuffed to a makeshift bed. His right arm has suffered some major damage. His few possessions are gone.He has no memory of getting there. The last thing Reacher can recall is the car he hitched a ride in getting run off the road. The driver was killed.His captors assume Reacher was the driver s accomplice and patch up his wounds as they plan to make him talk. A plan that will backfire spectacularly . . . There s only one Jack Reacher. Accept no substitutes. MICK HERRONAlthough the Jack Reacher novels can be read in any order, In Too Deep is the 29th book in the internationally bestselling series.

Objev podobné jako In Too Deep - Lee Child, Andrew Child

His memory might be gone. But his sense of justice is not.THE BRAND NEW REACHER NOVEL AND NUMBER ONE SUNDAY TIMES BESTSELLERReacher had no idea where he was. No idea how he had got there. But someone must have brought him. And shackled him. And whoever had done those things was going to rue the day. That was for damn sure.Jack Reacher wakes up, alone, in the dark, handcuffed to a makeshift bed. His right arm has suffered some major damage. His few possessions are gone. He has no memory of getting there.The last thing Reacher can recall is the car he hitched a ride in getting run off the road. The driver was killed.His captors assume Reacher was the driver s accomplice and patch up his wounds as they plan to make him talk.A plan that will backfire spectacularly . . . There s only one Jack Reacher. Accept no substitutes. MICK HERRON It s no wonder Jack Reacher is everyone s favourite rebel hero. KARIN SLAUGHTER One of the truly memorable tough-guy heroes in recent fiction. JEFFERY DEAVERAlthough the Jack Reacher novels can be read in any order, In Too Deep is the 29th book in the internationally bestselling series.Number 1 Sunday Times bestseller, October 2024

Objev podobné jako In Too Deep - Lee Child, Andrew Child

Audiokniha: Když v podhůří Appalačských hor zmizí za záhadných okolností církevní sbor, dávají bizarní stopy krveprolití tušit, že tuto tragédii má na svědomí snad sám ďábel. FBI má ovšem eso v rukávu – agentku Jessicu Blackwoodovou, bývalou nadanou kouzelnici z proslulé dynastie iluzionistů, která přednedávnem vyřešila případ tajemného Čaroděje a která díky svému nadání i zkušenostem dokáže rozpoznat, když věci nejsou takové, jaké se zdají být. Jessica je přesvědčená, že klíčem k záhadě je stará magnetofonová kazeta, a rozplétáním událostí, jež jsou na nahrávce zachycené, odhalí něco hodně znepokojivého – čin s dalekosáhlými důsledky. Mladá agentka se pouští po stopách zla, vedoucích ze Západní Virginie do Mexika, Miami, a dokonce až do posvátných síní Vatikánu, aby zastavila chladnokrevného vraha, posedlého smrtelným hříchem… „Svižný thriller, v němž jsou iluze zbraněmi dobra i zla.“ – Publishers Weekly. „Zápletka, která má spád, a inteligentní hlavní hrdinka ‒ to jsou ingredience adrenalinového příběhu s nečekaným zvratem. Skvělá četba.“ – Booklist. „Kniha, kterou prostě nemůžete odložit a u níž je vám líto, když otočíte poslední stránku.“ – Fresh Fiction. ANDREW MAYNE: Je autorem bestsellerů The Naturalist (Šelma, 2018), Looking Glass (Hračkář, 2019), Murder Theory (Teorie vraždy, 2019), Dark Pattern (Temný vzorec, 2020), The Girl Beneath the Sea (Dívka pod hladinou, 2020), Black Coral (Černý korál, 2022), Angel Killer (Vrah andělů, 2022) a Sea Storm (Námořní bouře, 2023; vše Kalibr). Byl nominován na cenu Edgar, je hvězdou televizního pořadu Don’t Trust Andrew Mayne a rovněž vystupuje jako kouzelník – první světové turné jako iluzionista absolvoval, když byl ještě teenager, a posléze spolupracoval s takovými legendami, jako jsou Penn Teller, David Blaine nebo David Copperfield. Uvádí také podcast Weird Things. V potápěčském obleku, který využívá umělou inteligenci a jenž si sám navrhl pro speciální díl po řadu Shark Week nazvaný Andrew Mayne: Ghost Diver, plaval po boku velkých bílých žraloků. www.andrewmayne.com JANA STRYKOVÁ: Narodila se v Brně, dnes ale žije se svou rodinou v Praze. Po jevišti se poprvé rozeběhla ve čtyřech letech, kdy jako členka dětského sboru Mahenova divadla účinkovala v operetě Polská krev. Na gymnáziu navštěvovala dramatický kroužek pod vedením Dany Hlaváčové a hrála amatérské divadlo ve spolku Misery Loves Company. V roce 2003 obdržela Cenu Valtra Tauba určenou pro nejlepší absolventy herectví na DAMU. Jana působila v řadě divadel, jako je např. Divadlo F. X. Šaldy Liberec, Švandovo divadlo, Divadlo na Vinohradech a od září 2017 účinkuje v Národním divadle v Praze. Na televizní obrazovce se Jana objevila v mnoha seriálech, jako je např. Ordinace v růžové zahradě, Tátové na tahu, V.I.P. vraždy nebo ve filmech Bludičky, Zakázané uvolnění, Hodinový manžel a mnoho dalších. Andrew Mayne: Jméno ďábla | Překlad Milan Lžička | Čte Jana Stryková| Režie Jan Drbohlav | Zvuk, střih a mastering Jakub Jedlička | Hudba Petr Hanzlík | Natočeno ve studiu BEEP | Grafiku CD podle knižní předlohy adaptovala Jana Rybová | Produkce Studio BEEP – Petra Krausová | Supervize Alena Brožová | Vydala Euromedia Group, a. s. – Témbr, v říjnu 2023. NAME OF THE DEVIL Copyright © 2015 by Andrew Mayne | Translation © Milan Lžička, 2023 | All rights reserved | Vydala Euromedia Group, a. s. - v edici Kalibr v roce 2023.

Objev podobné jako Jméno ďábla - Andrew Mayne - audiokniha

Origins Dr. Andrew Weil for Origins™ Mega-Mushroom Fortifying Emulsion with Reishi and Seabuckthorn, 100 ml, Pleťové krémy pro ženy, Probuďte svou pleť k životu Chcete vidět výsledky již po prvním použití? Díky jedinečné rostlinné technologii zklidňující a hydratační emulze Origins Dr. Andrew Weil for Origins™ Mega-Mushroom Fortifying Emulsion with Reishi and Seabuckthorn chrání pleť před viditelným poškozením modrým světlem a zároveň posiluje její přirozenou bariéru. Výsledkem je hedvábně jemná, hydratovaná a zářivá pleť. Vlastnosti: obnovuje a posiluje kožní bariéru uzamyká vlhkost v pleti na dlouhých 48 hodin zklidňuje podráždění a snižuje zarudnutí pleti chrání pleť před poškozením volnými radikály způsobenými modrým světlem zlepšuje jas, hebkost a pružnost pleti Složení: houba reishi – pomáhá zklidňovat pleť fermentovaná houba čaga – redukuje podráždění rakytník – chrání před volnými radikály a účinky modrého světla kyselina hyaluronová – poskytuje intenzivní hydrataci a vyhlazení rostlinný glycerin – pomáhá udržovat hydrataci skvalan – dodává pleti hebkost organický olivový olej – vyživuje pleť neobsahuje minerální oleje vhodné pro vegany Jak aplikovat: Emulzi Origins Dr. Andrew Weil for Origins™ Mega-Mushroom Fortifying Emulsion with Reishi and Seabuckthorn naneste na čistou a suchou pleť každé ráno a večer. Jemně vmasírujte, dokud se zcela nevstřebá. nbsp; Notino tip: Svou pleť nejprve očistěte zjemňující a zklidňující pleťovou vodou Origins Dr. Andrew Weil for Origins™ Mega-Mushroom Relief amp; Resilience Soothing Treatment Lotion.

Objev podobné jako Origins Dr. Andrew Weil for Origins™ Mega-Mushroom Fortifying Emulsion with Reishi and Seabuckthorn zklidňující a hydratační emulze 100 ml

Závěsné svítidlo Markslöjd Andrew černé – designová dominanta pro váš interiérZávěsné svítidlo Markslöjd Andrew v černém provedení je ideální volbou pro všechny, kdo hledají výrazné a moderní osvětlení. Svojí precizní kombinací matně černého kovu a šesti velkých čirých skleněných koulí dokáže okamžitě upoutat pozornost a zároveň dodat vašemu prostoru jedinečný charakter. Svítidlo zaujme nejen v obývacím pokoji, ale také nad jídelním stolem, v reprezentativních halách nebo v moderních pokojích.Výhody a klíčové vlastnosti Moderní design: Elegantní kombinace matné černé a čirého skla působí luxusně a nadčasově. Šest světelných bodů: Užijte si rovnoměrné a dostatečně silné osvětlení i ve větších místnostech. Kvalitní materiály: Tělo z pevného železa, stínidla ze skla – dlouhá životnost a snadná údržba. Univerzální použití: Vhodné nad jídelní stůl, do obývacího pokoje, pracovny nebo vstupní haly. Snadná instalace: Zavěšení na hák, klasická svorkovnice pro připojení k elektrické síti (230 V).Technické parametry Markslöjd Andrew Patice: 6× G9 (zdroj není součástí balení) Maximální výkon zdroje: 6× 5 W LED Stupeň krytí: IP20 (vhodné do interiéru) Rozměry: Průměr 75 cm, výška 60 cm Materiál: Železo, sklo Barva: černá (konstrukce), transparentní (stínidla) Hmotnost: 6,8 kg Možnost stmívání: Ne (závisí na použitém zdroji a externím stmívači) Bezpečnostní třída: IDoporučení od architektaSvítidlo Andrew doporučuji kombinovat s minimalistickým nebo industriálním nábytkem. Pro maximální světelný komfort volte kvalitní LED žárovky G9 s teplotou chromatičnosti 2700–3000 K, která navodí příjemnou atmosféru. Díky větším rozměrům vynikne nejlépe v prostornějších interiérech nebo jako centrální osvětlení.Trust badges garance Záruka: 3 roky Certifikace: Výrobek splňuje požadavky bezpečnostní třídy I a evropské standardy (CE)Často kladené dotazy (FAQ) Jaký typ žárovky zvolit? Doporučujeme kvalitní LED žárovky G9 do maximálního výkonu 5 W na jednu patici. Pro úsporu energie a dlouhou životnost vybírejte žárovky s minimálním příkonem a dlouhou životností. Lze svítidlo stmívat? Svítidlo nemá vestavěnou stmívací funkci, ale lze použít stmívatelné LED žárovky a externí stmívač kompatibilní s G9 LED.Ke stažení Návod k instalaci (PDF) Výkres a rozměry (PDF)

Objev podobné jako Markslöjd Andrew závěsné svítidlo černé

Audiokniha: Agentka Jessica Blackwoodová vyřešila už dva velké případy a jako vycházející hvězda FBI se stále musí vyrovnávat se svou nekonvenční minulostí iluzionistky. Pravidelně se teď také radí se svým excentrickým dědečkem, někdejším skvělým kouzelníkem, jehož vnímá jako svého učitele, přestože ho kdysi nemohla vystát. Zničehonic se ovšem rutinní sledovačka změní v drama a Jessica musí bojovat o život, když se na místě objeví vyšinutá žena s dítětem v náručí a vyhrožuje, že ho zabije. Téhož dne se krátce po silném zemětřesení, které zasáhne východní pobřeží, začne po internetu šířit podivné video, na němž fyzik Peter Devon, nositel Nobelovy ceny, který už je však osm let po smrti, předpovídá místo i datum zemětřesení. A nedlouho poté je nalezena mrtvola neznámé ženy, která popisem odpovídá útočnici, s níž se Jessica střetla. Vyšetřování série zdánlivě nesouvisejících, ale stejně tak bizarních a temných zločinů zavede Jessicu do coloradské pouště a do vísky, po níž se jednoduše slehla zem, a mladá agentka zjišťuje, že se bude muset popasovat s něčím chmurnějším a mocnějším, než by kdokoliv čekal. S něčím tak zvráceným, že za tím může stát jen jediný člověk – Čaroděj. Audiokniha: Andrew Mayne: Pád do temnoty | Překlad Milan Lžička | Čte Jana Stryková | Režie Jan Drbohlav | Zvuk, střih a mastering Zuzana Švancarová | Hudba Petr Hanzlík | Natočeno ve studiu BEEP | Grafiku podle knižní předlohy adaptovala Jana Rybová | Produkce Studio BEEP – Petra Krausová | Supervize Alena Brožová | Vydala Euromedia Group, a. s. – Témbr, v prosinci 2024. Nahrávka vznikla dle knižní předlohy: Black Fall Copyright © 2017 by AndrewMayne.com LLC | Translation © Milan Lžička, 2024 | Obálku navrhl David Dvořák | All rights reserved. | Vydala Euromedia Group, a. s. - v edici Kalibr v roce 2024. Andrew Mayne je autorem bestsellerů The Naturalist (česky Šelma, 2018), Looking Glass (Hračkář, 2019), Murder Theory (Teorie vraždy, 2019), Dark Pattern (Temný vzorec, 2020), The Girl Beneath The Sea (Dívka pod hladinou, 2021), Black Coral (Černý korál, 2022), Angel Killer (Vrah andělů, 2022), Name of The Devil (Jméno ďábla, 2023) nebo Sea Storm (Námořní bouře, 2023). Andrew byl nominován na cenu Edgar, je hvězdou televizního pořadu Nevěřte Andrewu Mayneovi a rovněž vystupuje jako kouzelník – první světové turné v roli iluzionisty absolvoval ještě jako náctiletý a posléze pracoval v zákulisí pro duo Penn a Teller, pro Davida Blaina i Davida Copperfielda. Na britském Amazonu se Andrew stal pátým nejprodávanějším nezávislým autorem roku, a aby toho nebylo málo, uvádí také podcast Weird Things. Další podrobnosti se o něm lze dozvědět na jeho webové stránce www.AndrewMayne.com. Jana Stryková se narodila v Brně, dnes ale žije se svou rodinou v Praze. Po jevišti se poprvé rozeběhla ve čtyřech letech, kdy jako členka dětského sboru Mahenova divadla účinkovala v operetě Polská krev. Na gymnáziu navštěvovala dramatický kroužek pod vedením Dany Hlaváčové a hrála amatérské divadlo ve spolku Misery Loves Company. V roce 2003 obdržela Cenu Valtra Tauba určenou pro nejlepší absolventy herectví na DAMU. Jana působila v řadě divadel, jako je např. Divadlo F. X. Šaldy Liberec, Švandovo divadlo, Divadlo na Vinohradech a od září 2017 účinkuje v Národním divadle v Praze. Na televizní obrazovce se Jana objevila v mnoha seriálech, jako je např. Ordinace v růžové zahradě, Tátové na tahu, V.I.P. vraždy nebo ve filmech Bludičky, Zakázané uvolnění, Hodinový manžel a mnoho dalších.

Objev podobné jako Pád do temnoty - Andrew Mayne - audiokniha

From the No.1 Sunday Times bestselling author of The Ashes of London comes the next book in the phenomenally successful series following James Marwood and Cat Lovett.Over 1 Million Andrew Taylor Novels Sold!A dangerous secret lies beneath Whitehall Palaceâ ¦Brother against brother. Father against son. Friends turned into enemies. No one in England wants a return to the bloody days of the Civil War. But Oliver Cromwellâ ™s son, Richard, has abandoned his exile and slipped back into England. The consequences could be catastrophic.James Marwood, a traitorâ ™s son turned government agent, is tasked with uncovering Cromwellâ ™s motives. But his assignment is complicated by his friend â “ the regicideâ ™s daughter, Cat Lovett â “ who knew the Cromwells as a child, and who now seems to be hiding a secret of her own about the family.Both Marwood and Cat know they are putting themselves in great danger. And when they find themselves on a top secret mission in the Palace of Whitehall, they realize they are risking their livesâ ¦and could even be sent to the block for treason.Praise for Andrew Taylorâ ˜One of the best historical crime writers todayâ ™ The Timesâ ˜If you like C. J. Sansom, or Hilary Mantel, youâ ™ll love Andrew Taylorâ ™ Peter Jamesâ ˜Effortlessly authenticâ ¦grippingâ ¦moving and believable. An excellent workâ ™ C. J. Sansomâ ˜This is historical crime fiction at its dazzling bestâ ™ Guardianâ ˜One of the best historical novelists aroundâ ™ Sunday Timesâ ˜A breathtakingly ambitious picture of an eraâ ™ Financial Timesâ ˜A masterclass in writing for the genreâ ™ Ann Cleevesâ ˜Andrew Taylor is one of our finest storytellers Antonia Hodgsonâ ˜Vivid and compellingâ ™ Observerâ ˜A novel filled with intrigue, duplicity, scandal and betrayal, whose author now vies with another master of the genre, C. J. Sansomâ ™ Spectatorâ ˜Taylor brings the 17th century to life so vividly that one can almost smell itâ ™ Guardianâ ˜A most artful and delightful book, that will both amuse and chillâ ™ Daily Telegraph

Objev podobné jako The Last Protector - Andrew Taylor

When the phenomenal success of GOD S SMUGGLER made it too dangerous for his contacts in the underground church, Brother Andrew decided he could not return to Eastern Europe. He quietly turned his attention the the Middle East, and for the last thirty-five years he has been serving the Christian Church there, as well as witnessing to Jews and Muslims.His impassioned message is that there is a radical Christian approach to the stalemate of Middle East conflict. Only the gospel of love has the answer, and Christians are called to allow God to use them to demonstrate the example of Jesus.Now available with a fantastic new look to coincide with the B format edition of Brother Andrew s bestselling SECRET BELIEVERS, LIGHT FORCE brings Brother Andrew s story right up to date. It is every bit as exciting as GOD S SMUGGLER, as Andrew has put his life on the line time and again in God s service.

Objev podobné jako Light Force - Brother Andrew, Al Janssen

‘Passion, positivity and precision ... and always be willing to learn something new.’Athlete Andrew Henderson was just sixteen years old when a horrific rugby injury put paid to his career in the game. So he turned his attention to football – more specifically, freestyling football skills – and never looked back. Now a five-time World Freestyling Champion and the UK Freestyle football champion for eight years running, in this unique manual Andrew brings together all his expertise and advice to help make you a betterfootballer.Packed with tips, tricks and over 200 colour photographs, Andrew reveals how hard work, dedication and flair allowed him to become a master on the football pitch and beyond. Having worked with Cristiano Ronaldo, impressed the likes of David Beckham and Neymar, to performing at the opening ceremonies of the Olympics and various World Cups around the world, he is now sharing all his secrets and famous freestyling skills to help you improve your football techniques and take them onto the pitch.Interspersed with the jaw-dropping tricks, guidance on tackling, fundamental skills and tips on advancing your expertise, Andrew’s passionate advice about following a dream and overcoming adversity prove that both enthusiasm and patience play a major part in any sporting arena. This isn’t only about teaching the physical elements but learning from a master about how to focus your mentality to bring flair, passion and precision to your game.

Objev podobné jako How to Be a Better Footballer - Henderson Andrew

Andrew Gold is the new Jon Ronson. Smart, funny, brave and deeply thoughtful, The Psychology of Secrets is an absolute must read - Will Storr, bestselling author of The Status Game and The Science of StorytellingCult leaders, murderers, psychopaths â “ and you. Take a deep dive into the bizarre psychology of secrecy with Andrew Gold, award-winning investigative journalist and host of Heretics.We all keep secrets. 97 per cent of us are hiding a secret right now, and on average we each hold thirteen at any one time. Thereâ ™s a one-in-two chance that those secrets involve a breach of trust, a lie or a financial impropriety. They are the stuff of gossip, of novels and of classic dramas; secrets form a major part of our hidden inner lives.Andrew Gold knows this better than anyone. As a public figure, he has found himself the unwitting recipient of hundreds of strangers most private revelations. This set him on a journey to understand this critical part of our societies and lives. Why do we keep secrets? Why are we fascinated by those of others? What happens to our mind when we confess?Drawing from psychology, history, social science, philosophy and personal interviews, The Psychology of Secrets is a rollicking journey through the history of secrecy.-- Andrew Gold is - but should not be - one of our cultureâ ™s best kept secrets. He is a truly edgy journalist, broadcaster and writer - David Baddiel, bestselling author of The God Desire

Objev podobné jako The Psychology of Secrets - Andrew Gold

Origins Dr. Andrew Weil for Origins™ Mega-Mushroom Micellar Cleanser, 200 ml, Micelární vody pro ženy, Vyzkoušejte blahodárné účinky mnoha přírodních extraktů. Micelární voda Origins Dr. Andrew Weil for Origins™ Mega-Mushroom Micellar Cleanser obsahuje charakteristickou směs Mega-Mushroom, která zklidňuje a posiluje pleť. Jemně, ale přesto účinně odstraňuje nečistoty a make-up a zanechává pleť svěží a jemnou. Vlastnosti: šetrně čistí pleť podporuje odolnost pleti pomáhá zklidňovat podrážděnou pleť Složení: extrakt z houby reishi extrakt z řasy Hypnea musciformis a Gellidiela acerosa extrakt z kurkumy, ze zázvoru, z ostropestřce mariánského, bazalky svaté a housenice čínské extrakt z okurky, brusinek, borůvek a z goji olej pomerančový, levandulový, pačuli, mandarinkový, gerániový a slunečnicový kyselina hyaluronová extrakt z kvasnic bez mýdla a alkoholu Jak aplikovat: Malé množství micelární vody Origins Dr. Andrew Weil for Origins™ Mega-Mushroom Micellar Cleanser nalejte na vatový tamponek a jemně otírejte obličej a krk.

Objev podobné jako Origins Dr. Andrew Weil for Origins™ Mega-Mushroom Micellar Cleanser čisticí micelární voda 200 ml

Ide o jednu z najdôležitejších diskusií v súčasnej cirkvi. A najkontroverznejších. Andrew Marin do nej vnáša svieži, vľúdny a novátorský hlas. Nevníma túto tému len ako nejakú pálčivú „otázku“ – vidí za ňou tvár, priateľa, Božie dieťa. Vidí za ňou Ježiša, ktorého láska je pre mnohých ťažko uchopiteľná, pretože u jeho nasledovníkov sa stretli s niečím iným.Andrew nám pripomína, že či už sme ladení konzervatívne alebo liberálne, môžeme mať skvelé myšlienky, a predsa byť krutí a samospravodliví. To, že sme kresťania, však ľudia nespoznajú podľa toho, čo citujeme, ale podľa našej lásky.Na konci knihy vás Andrew nebude žiadať, aby ste súhlasili s jeho názormi na gejskú a lesbickú orientáciu alebo životný štýl. Vlastne vás nezahrnie ani množstvom polemických názorov. Pokúsi sa pomôcť vám pochopiť, čo sa naučil počúvaním s otvoreným a chápavým srdcom voči lesbám a gejom. A tiež sa pokúsi pomôcť vám reagovať na gejov a lesby vo vašom svete zrelšie a chápavejšie. Na záver vás požiada, aby ste sa zhodli na jednej hlavnej veci: že pre skutočných Ježišových nasledovníkov je jedinou správnou cestou orientácia a životný štýl lásky.Brian McLarenAndrew Marin je prezidentom a zakladateľom The Marin Foundation. Je ženatý, má dve deti. Dvanásť rokov žil v časti Chicaga známej ako Boystown (dnes Northalsted), kde žije veľa LGBT+ ľudí. Dnes žije vo Washingtone, D.C. a venuje sa poradenstvu.

Objev podobné jako Láska je orientácia - Andrew Marin

Koupelnové LED svítidlo Rabalux Andrew 12W IP44 – Moderní volba pro vaši koupelnuNástěnné koupelnové svítidlo Rabalux Andrew LED 12W přináší do moderních interiérů nejen elegantní design, ale i vysokou funkčnost a bezpečnost. Díky svému jednoduchému, matně bílému provedení a kvalitním materiálům (kov/plast) je ideální volbou nad zrcadlo nebo umyvadlo, kde zajistí příjemné, rovnoměrné osvětlení bez oslnění.Hlavní přednosti svítidla Moderní vzhled – Matná bílá barva a minimalistické linie skvěle doplní současné koupelnové trendy. LED technologie – Úsporný vestavěný zdroj s výkonem 12 W a životností až 20 000 hodin. Kvalitní osvětlení – Světelný tok 820 lm a teplota světla 3000 K (příjemná teplá bílá) pro každodenní komfort. Bezpečnost v koupelně – Krytí IP44 chrání proti stříkající vodě a vniknutí drobných předmětů. Snadná instalace – Ideální nad zrcadlo, kde zajistí optimální světelné podmínky pro hygienu i relax. Ekologicky šetrné – LED technologie šetří energii a má nižší provozní náklady.Technické parametry Příkon: 12 W Světelný tok: 820 lm Barva světla: 3000 K (teplá bílá) Životnost: 20 000 h Energetická třída: G Krytí: IP44 Rozměry: délka 490 mm, výška 65 mm, hloubka 95 mm Hmotnost: 820 g Napětí: 230V, 50Hz Materiál: kov / plastDoporučení architektaToto svítidlo doporučuji instalovat zejména nad zrcadlo v koupelně, kde poskytne dostatek světla pro každodenní hygienu i náročnější kosmetické úkony. Díky neutrálnímu designu jej lze snadno kombinovat s dalšími prvky moderních koupelen a jeho vyšší krytí IP44 zaručuje odolnost vůči vlhkosti.Trust badges garance Životnost LED: 20 000 hodin Záruka: 5 let Certifikace: CE Bezpečnost: IP44 – vhodné do koupelnyFAQ – Často kladené otázky Je možné svítidlo použít přímo nad zrcadlo? Ano, svítidlo je konstruováno pro montáž nad zrcadlo i do vlhkého prostředí, jeho krytí IP44 zajišťuje bezpečnost vůči stříkající vodě. Obsahuje svítidlo zabudovaný zdroj světla? Ano, LED zdroj je součástí balení a není třeba dokupovat žárovku. Rabalux Andrew LED 12W je spolehlivou a stylovou volbou pro každého, kdo hledá kvalitní, úsporné a elegantní osvětlení do koupelny.

Objev podobné jako Rabalux koupelnové svítidlo Andrew LED 12W IP44 5782

Build your strongest-ever portfolio from anywhere in the world Now in its third edition, Millionaire Expat is the world⠙s most trusted, bestselling guide for expat investors. It shows readers how to protect themselves from financial sharks and build effective portfolios that maximize profits and tax efficiency. This updated guide includes model portfolios of ETFs or index funds. It recommends subtle differences for investors based on nationality, while explaining why all-in-one portfolio funds are even simpler and more profitable than individual ETFs. Millionaire Expat also provides investment models for socially responsible funds. Best of all, this book is specific. Author Andrew Hallam doesn⠙t just offer theory. He shows you exactly what to buy and where to buy it from. He explains how much you should sell each year, upon retirement, and discusses repatriation: showing how different countries deal with the taxation of portfolios that were built abroad.  And if you⠙re looking for a hands-free approach, Millionaire Expat offers something for you as well: lists of roboadvisors and full-service financial firms that offer guidance and build portfolios of ETFs and index funds. But what if you started investing late and can⠙t afford to retire? In that case, Andrew Hallam has you covered. He profiles several low-cost countries that are popular with expats. He explains what countries are great for Global Nomads and for retirees looking for tax breaks, safety, solid health care systems and a low-cost, enjoyable standard of living. Millionaire Expat (3rd edition) is an entertaining guide, showing readers how to maximize their money and their life satisfaction based on simple, smart investing and their choice of retirement destination. Author Andrew Hallam was a high school teacher who built a million-dollar portfolio⠔on a teacher s salary. He knows how everyday people can achieve success in the market. In Millionaire Expat, he tailors his best advice to the unique needs of those living overseas to give you the targeted, real-world guidance you need.

Objev podobné jako Millionaire Expat - Andrew Hallam