inspiring deep learning with metacognition nathan burns

Understand what metacognition is and how you can apply it to your secondary school teaching to support deep and effective learning in your classroom. Metacognition is a popular topic in teaching and learning debates, but it’s rarely clearly defined and can be difficult for teachers to understand how it can be applied in the classroom. This book offers a clear introduction to applying metacognition in secondary teaching, exploring the ‘what’, ‘when/how’ and ‘why’ of using metacognition in classrooms with real life examples of how this works in practice. This is a detailed and accessible resource that offers guidance that teachers can start applying to their own lesson planning immediately, across secondary subjects. Nathan Burns is the founder of @MetacognitionU and has written metacognitive teaching resources for TES and Oxford University Press. He is Head of Maths in a Derbyshire school. Â

Objev podobné jako Inspiring Deep Learning with Metacognition - Nathan Burns

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 • Using the PyTorch tensor API • Understanding automatic differentiation in PyTorch • Training deep neural networks • Monitoring training and visualizing results • 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 ... Unknown localization key: "more"

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

Stable Diffusion, ChatGPT, Whisper - these are just a few examples of incredible applications powered by developments in machine learning. Despite the ubiquity of machine learning applications running in production, there are only a few viable language choices for data science and machine learning tasks. Elixir''s Nx project seeks to change that. With Nx, you can leverage the power of machine learning in your applications, using the battle-tested Erlang VM in a pragmatic language like Elixir. In this book, you''ll learn how to leverage Elixir and the Nx ecosystem to solve real-world problems in computer vision, natural language processing, and more.The Elixir Nx project aims to make machine learning possible without the need to leave Elixir for solutions in other languages. And even if concepts like linear models and logistic regression are new to you, you''ll be using them and much more to solve real-world problems in no time.Start with the basics of the Nx programming paradigm - how it differs from the Elixir programming style you''re used to and how it enables you to write machine learning algorithms. Use your understanding of this paradigm to implement foundational machine learning algorithms from scratch. Go deeper and discover the power of ... Unknown localization key: "more"

Objev podobné jako Machine Learning in Elixir - Sean Moriarity

Vtech hodinky s aplikací Learning Lodge
bezpečný dětský hrnek Bear with me Blue
hrneček Bear with me Pink KikkaBoo
Click with Friends 3 angličtina
přepracované vydání Start with Click
skládací skříň s policí Deep Black
skládací skříň z fólie PEVA Deep Black
skříň Wenko Deep Black 150x50x75 cm
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bronzující pudr Guerlain Terracotta 05 Deep Warm
L'Oréal Paris odstín 904 Deep Glow

This book is a practical guide offering new ways to fix many typical day-to-day issues in schools using metacognition to offer effective and efficient solutions. Discover new ways to enhance your own teaching with metacognition and how to apply it to many common aspects of teaching and learning. Every chapter is written by a different education expert and takes a solution-focused approach exploring metacognitive strategies and ideas for the classroom. Key topics include: Smart revision strategies Nuanced and effective feedback The power of modelling answers Student motivation and resilience Supporting struggling writers Integrating metacognition across the curriculum And much more!

Objev podobné jako Teaching Hacks: Fixing Everyday Classroom Issues with Metacognition

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 ... Unknown localization key: "more"

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

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. • Foundational reinforcement learning concepts and methods • The most popular deep reinforcement learning agents solving high-dimensional environments • 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 ... Unknown localization key: "more"

Objev podobné jako Grokking Deep Reinforcement Learning - Miguel Morales

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 • Models for textual similarity • Deep memory-based NLP • Semantic role labeling • 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. He’s the technical coordinator of two large European Union-funded research security-related ... Unknown localization key: "more"

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

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 success—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 ... Unknown localization key: "more"

Objev podobné jako Learning Deep Learning - Magnus Ekman

The Science of Deep Learning emerged from courses taught by the author that have provided thousands of students with training and experience for their academic studies, and prepared them for careers in deep learning, machine learning, and artificial intelligence in top companies in industry and academia. The book begins by covering the foundations of deep learning, followed by key deep learning architectures. Subsequent parts on generative models and reinforcement learning may be used as part of a deep learning course or as part of a course on each topic. The book includes state-of-the-art topics such as Transformers, graph neural networks, variational autoencoders, and deep reinforcement learning, with a broad range of applications. The appendices provide equations for computing gradients in backpropagation and optimization, and best practices in scientific writing and reviewing. The text presents an up-to-date guide to the field built upon clear visualizations using a unified notation and equations, lowering the barrier to entry for the reader. The accompanying website provides complementary code and hundreds of exercises with solutions.

Objev podobné jako The Science of Deep Learning - Iddo Drori

Humans learn best from feedback—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 you’ll need to implement it into your own projects. Key features • Structuring problems as Markov Decision Processes • Popular algorithms such Deep Q-Networks, Policy Gradient method and Evolutionary Algorithms and the intuitions that drive them • Applying reinforcement learning algorithms to real-world problems Audience You’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 that’s not all it can do! Alexander Zai is a Machine Learning Engineer at Amazon AI working on ... Unknown localization key: "more"

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

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 ... Unknown localization key: "more"

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

An authoritative, accessible, and up-to-date treatment of deep learning that strikes a pragmatic middle ground between theory and practice.Deep learning is a fast-moving field with sweeping relevance in today’s increasingly digital world. Understanding Deep Learning provides an authoritative, accessible, and up-to-date treatment of the subject, covering all the key topics along with recent advances and cutting-edge concepts. Many deep learning texts are crowded with technical details that obscure fundamentals, but Simon Prince ruthlessly curates only the most important ideas to provide a high density of critical information in an intuitive and digestible form. From machine learning basics to advanced models, each concept is presented in lay terms and then detailed precisely in mathematical form and illustrated visually. The result is a lucid, self-contained textbook suitable for anyone with a basic background in applied mathematics.Up-to-date treatment of deep learning covers cutting-edge topics not found in existing texts, such as transformers and diffusion modelsShort, focused chapters progress in complexity, easing students into difficult concepts Pragmatic approach straddling theory and practice gives readers the level of detail required to implement naive versions of modelsStreamlined presentation separates critical ideas from background context and extraneous detailMinimal mathematical prerequisites, extensive illustrations, and practice problems make challenging ... Unknown localization key: "more"

Objev podobné jako Understanding Deep Learning - Simon J.D. Prince

Deep reinforcement learning has attracted considerable attention recently. Impressive results have been achieved in such diverse fields as autonomous driving, game playing, molecular recombination, and robotics. In all these fields, computer programs have taught themselves to understand problems that were previously considered to be very difficult. In the game of Go, the program AlphaGo has even learned to outmatch three of the world''s leading players.Deep reinforcement learning takes its inspiration from the fields of biology and psychology. Biology has inspired the creation of artificial neural networks and deep learning, while psychology studies how animals and humans learn, and how subjects'' desired behavior can be reinforced with positive and negative stimuli. When we see how reinforcement learning teaches a simulated robot to walk, we are reminded of how children learn, through playful exploration. Techniques that are inspired by biology and psychology work amazingly well in computers: animal behavior and the structure of the brain as new blueprints for science and engineering. In fact, computers truly seem to possess aspects of human behavior; as such, this field goes to the heart of the dream of artificial intelligence. These research advances have not gone unnoticed by educators. Many universities have begun offering courses ... Unknown localization key: "more"

Objev podobné jako Deep Reinforcement Learning - Aske Plaat

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

Deep Learning Crash Course goes beyond the basics of machine learning to delve into modern techniques and applications of great interest right now, and whose popularity will only grow in the future. The book covers topics such as generative models (the technology behind deep fakes), self-supervised learning, attention mechanisms (the tech behind ChatGPT), graph neural networks (the tech behind AlphaFold), and deep reinforcement learning (the tech behind AlphaGo). This book bridges the gap between theory and practice, helping readers gain the confidence to apply deep learning in their work.

Objev podobné jako Deep Learning Crash Course - Benjamin Midtvedt, Jesus Pineda, Giovanni Volpe

Computer vision-based crack-like object detection has many useful applications, such as inspecting/monitoring pavement surface, underground pipeline, bridge cracks, railway tracks etc. However, in most contexts, cracks appear as thin, irregular long-narrow objects, and often are buried in complex, textured background with high diversity which make the crack detection very challenging. During the past a few years, deep learning technique has achieved great success and has been utilized for solving a variety of object detection problems.This book discusses crack-like object detection problem comprehensively. It starts by discussing traditional image processing approaches for solving this problem, and then introduces deep learning-based methods. It provides a detailed review of object detection problems and focuses on the most challenging problem, crack-like object detection, to dig deep into the deep learning method. It includes examples of real-world problems, which are easy to understand and could be a good tutorial for introducing computer vision and machine learning.

Objev podobné jako Deep Learning for Crack-Like Object Detection - Heng-Da Cheng, Kaige Zhang

Holidays with Hitler tells the story of German leisure time and state-sponsored fun under the Nazi regime. Nathan Morley looks at consumerism, entertainment and travel in German society, and offers a vivid portrait of what it was like to visit as a foreign tourist seeking fun in a totalitarian state.An important part of Nazi policy was the vast Strength through Joy programme, headed by Dr Robert Ley – a brash and fanatical party member. Although Strength through Joy is best remembered for introducing the Volkswagen Beetle, it also allowed fourteen million people to enjoy annual vacations at bargain basement prices while improving the health of the population by encouraging running, hiking, swimming, and active family holidays. With millions of working people paying monthly dues, the organization amassed a hefty fortune. On the island of Rügen in the Baltic Sea, a vast resort capable of accommodating 22,000 holidaymakers began construction in 1937 – the same year the Wilhelm Gustloff, the first Strength Through Joy vessel, was launched in Hamburg. With the arrival of the Second World War, the organisation adapted, the goal being the ‘cultural caretaking of the bomb-battered population and our soldiers’.Nathan Morley, employing meticulous research, tells the story not ... Unknown localization key: "more"

Objev podobné jako Holidays with Hitler - Nathan Morley

Harness the power of Tetris®, one of the world’s most popular puzzle games, to organize your home, office, and life!Powered by the principles of one of the world’s most popular puzzle games, Organizing with Tetris™ tackles the organization for every room in your home and even unexpected corners of your life. Board-certified professional organizer Kathi Burns and Tetris expert Morgan Shaver lay out accessible, strategic tips and teach you to follow the six organizational strategies of Tetris® alongside fun facts about the iconic game.Whether straightening, streamlining, or purging spaces “line by line,” this book will help you make difficult decisions to keep or discard as items are organized using the principles of Tetris to enhance your living situation as well as your overall way of life. Featuring all-new, Tetrimino-colored illustrations, learn to effectively target problem areas in your entryway, bathroom, office, kitchen, bedroom, living room, attic, garage, and basement to declutter in a fun, low-stress way. No matter what sort of space you live in, Organizing with Tetris offers practical tips to help you win the game of organization and ensure that, with enough practice, everything falls into place.HARNESS ‘THE TETRIS EFFECT’: Studies indicate that playing Tetris for extended periods ... Unknown localization key: "more"

Objev podobné jako Organizing with Tetris - Kathi Burns, Morgan Shaver

This book explores the benefits of deploying Machine Learning (ML) and Artificial Intelligence (AI) in the health care environment. The authors study different research directions that are working to serve challenges faced in building strong healthcare infrastructure with respect to the pandemic crisis. The authors take note of obstacles faced in the rush to develop and alter technologies during the Covid crisis. They study what can be learned from them and what can be leveraged efficiently. The authors aim to show how healthcare providers can use technology to exploit advances in machine learning and deep learning in their own applications. Topics include remote patient monitoring, data analysis of human behavioral patterns, and machine learning for decision making in real-time.

Objev podobné jako System Design for Epidemics Using Machine Learning and Deep Learning

This book investigates in detail the emerging deep learning (DL) technique in computational physics, assessing its promising potential to substitute conventional numerical solvers for calculating the fields in real-time. After good training, the proposed architecture can resolve both the forward computing and the inverse retrieve problems.Pursuing a holistic perspective, the book includes the following areas. The first chapter discusses the basic DL frameworks. Then, the steady heat conduction problem is solved by the classical U-net in Chapter 2, involving both the passive and active cases. Afterwards, the sophisticated heat flux on a curved surface is reconstructed by the presented Conv-LSTM, exhibiting high accuracy and efficiency. Additionally, a physics-informed DL structure along with a nonlinear mapping module are employed to obtain the space/temperature/time-related thermal conductivity via the transient temperature in Chapter 4. Finally, in Chapter 5, a series of the latest advanced frameworks and the corresponding physics applications are introduced.As deep learning techniques are experiencing vigorous development in computational physics, more people desire related reading materials. This book is intended for graduate students, professional practitioners, and researchers who are interested in DL for computational physics.

Objev podobné jako Deep Learning-Based Forward Modeling and Inversion Techniques for Computational Physics Problems - Qiang Ren, Yinpeng Wang

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

This book is a comprehensive guide suitable for beginners and experienced developers alike. It teaches readers how to master object-oriented programming (OOP) with Python and use it in real-world applications.Start by solidifying your OOP foundation with clear explanations of core concepts like use cases and class diagrams. This book goes beyond theory as you get practical examples with well-documented source code available in the book and on GitHub.This book doesn''t stop at the basics. Explore how OOP empowers fields like data persistence, graphical user interfaces (GUIs), machine learning, and data science, including social media analysis. Learn about machine learning algorithms for classification, regression, and unsupervised learning, putting you at the forefront of AI innovation.Each chapter is designed for hands-on learning. You''ll solidify your understanding with case studies, exercises, and projects that apply your newfound knowledge to real-world scenarios. The progressive structure ensures mastery, with each chapter building on the previous one, reinforced by exercises and projects.Numerous code examples and access to the source code enhance your learning experience. This book is your one-stop shop for mastering OOP with Python and venturing into the exciting world of machine learning and data science.

Objev podobné jako The Object-Oriented Approach to Problem Solving and Machine Learning with Python - Maha Hadid, Sujith Samuel Mathew, Shahbano Farooq, Mohammad Amin K

Deep Learning: A Visual Approach helps demystify the algorithms that enable computers to drive cars, win chess tournaments, and create symphonies, while giving readers the tools necessary to build their own systems to help them find the information hiding within their own data, create ''deep dream'' artwork, or create new stories in the style of their favorite authors.

Objev podobné jako Deep Learning - Andrew Glassner

Cognitive computing simulates human thought processes with self-learning algorithms that utilize data mining, pattern recognition, and natural language processing. The integration of deep learning improves the performance of Cognitive computing systems in many applications, helping in utilizing heterogeneous data sets and generating meaningful insights.

Objev podobné jako Deep Learning for Cognitive Computing Systems

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) – 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 ... Unknown localization key: "more"

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

This book illustrates complex concepts of full stack deep learning and reinforces them through hands-on exercises to arm you with tools and techniques to scale your project.

Objev podobné jako Deep Learning at Scale - Suneeta Mall

This step-by-step guide teaches you how to build practical deep learning applications for the cloud and mobile using a hands-on approach.

Objev podobné jako Practical Deep Learning for Cloud and Mobile - Anirudh Koul, Siddha Ganju, Meher Kasam

Create and sustain a culture of learning.If you read nothing else on learning, read these 10 articles by experts in the field. We''ve combed through hundreds of Harvard Business Review articles and selected the most important ones to help you keep your skills fresh and relevant, support continuous improvement on your team, and prepare everyone in the organization to thrive over the long term.This book will inspire you to:Cultivate relentless curiosityMagnify your strengths and make yourself indispensableNurture a growth mindset in yourself and othersDeliver actionable feedback to help every employee excelTransform today''s failure into tomorrow''s successReimagine your employee-development programBuild a learning organizationThis collection of articles includes "Learning to Learn," by Erika Andersen; "Making Yourself Indispensable," by John H. Zenger, Joseph R. Folkman, and Scott K. Edinger; "Find the Coaching in Criticism," by Sheila Heen and Douglas Stone; "Teaching Smart People How to Learn," by Chris Argyris; "The Feedback Fallacy," by Marcus Buckingham and Ashley Goodall; "The Leader as Coach," by Herminia Ibarra and Anne Scoular; "Strategies for Learning from Failure," by Amy C. Edmondson; "Learning in the Thick of It," by Marilyn Darling, Charles Parry, and Joseph Moore; "Is Yours a Learning Organization?" by David A. Garvin, Amy C. Edmondson, ... Unknown localization key: "more"

Objev podobné jako HBR's 10 Must Reads on Lifelong Learning (with bonus article "The Right Mindset for Success" with Carol Dweck) - Dweck Carol, Marcus Buckingham, Harva

This modern and self-contained book offers a clear and accessible introduction to the important topic of machine learning with neural networks. In addition to describing the mathematical principles of the topic, and its historical evolution, strong connections are drawn with underlying methods from statistical physics and current applications within science and engineering. Closely based around a well-established undergraduate course, this pedagogical text provides a solid understanding of the key aspects of modern machine learning with artificial neural networks, for students in physics, mathematics, and engineering. Numerous exercises expand and reinforce key concepts within the book and allow students to hone their programming skills. Frequent references to current research develop a detailed perspective on the state-of-the-art in machine learning research.

Objev podobné jako Machine Learning with Neural Networks - Bernhard Mehlig

A beautifully designed book full of creative ideas and fun activities to get your children outdoors, with a foreword by Chris Packham.Spending time outdoors and interacting with the elements gives our senses a host of stimuli that cannot be recreated indoors. Whether you’re splashing in muddy puddles, making shelters, foraging blackberries, playing hide and seek or watching birds, experiencing the natural world reduces stress, makes us feel alive and lays critical foundations for a healthy developing brain.Learning with Nature is ideal for parents, teachers and youth workers looking to enrich children’s learning through nature and teach them to enjoy and respect the great outdoors. Written by experienced Forest School practitioners, it is packed with more than 100 tried and tested games and activities suitable for groups of children aged between 3 and 16, which aim to help children develop key practical and social skills and gain a better awareness of the world. The book is well-organised and features step-by-step instructions, age guides, a list of resources needed, and invisible learning points.Explore, have fun, make things and learn about nature with this fantastic guide.

Objev podobné jako Learning with Nature - Anna Richardson, Marina Robb, Victoria Mew

I can move only with the aid of barrels of anti-inflammatory gel, sticking plasters and real ale anaesthetic. Martin and I descend from hours of walking to the small town of Middleton-in-Teesdale. I walk, stiff legged, into the campsite office and a plump, middle-aged woman looks up from her desk and can see the old timer is in trouble.“Oh, what a shame you weren’t here last week,” she says, pity radiating from behind her horn-rimmed specs. “You’ve missed him.”I look at her, puzzled.“Elvis!” she explains. “You missed Elvis.”Oh God, now I’m hallucinating…In Bothy Tales, the follow-up to The Last Hillwalker from bestselling mountain writer John D. Burns, travel with the author to secret places hidden amongst the British hills and share his passion for the wonderful wilderness of our uplands.From remote glens deep in the Scottish Highlands, Burns brings a new volume of tales – some dramatic, some moving, some hilarious – from the isolated mountain shelters called bothies. Meet the vivid cast of characters who play their games there, from climbers with more confidence than sense to a young man who doesn’t have the slightest idea what he’s letting himself in for…

Objev podobné jako Bothy Tales - John D. Burns

The “blockbuster” (The Guardian) New York Times bestseller, a shocking, definitive account of the 2020 election and the first year of the Biden presidency by two New York Times reporters, exposes the deep fissures within both parties as the country approaches a political breaking point.This is the authoritative, “deeply reported” (The Wall Street Journal) account of an eighteen-month crisis in American democracy that will be seared into the country’s political memory for decades to come. With stunning, in-the-room detail, New York Times reporters Jonathan Martin and Alexander Burns show how both our political parties confronted a series of national traumas, including the coronavirus pandemic, the January 6 attack on the Capitol, and the political brinksmanship of President Biden’s first year in the White House. From Donald Trump’s assault on the 2020 election and his ongoing campaign of vengeance against his fellow Republicans to the behind-the-scenes story of Biden’s selection of Kamala Harris as his running mate and his bitter struggles to unite the Democratic Party, this book exposes the degree to which the two-party system has been strained to the point of disintegration. More than at any time in recent history, the long-established traditions and institutions of American politics are ... Unknown localization key: "more"

Objev podobné jako This Will Not Pass - Alexander Burns, Jonathan Martin

Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions.

Objev podobné jako Introduction to Machine Learning with Python - Andreas C. Mueller

This class-tested textbook will provide in-depth coverage of the fundamentals of machine learning, with an exploration of applications in information security. The book will cover malware detection, cryptography, and intrusion detection. The book will be relevant for students in machine learning and computer security courses.

Objev podobné jako Introduction to Machine Learning with Applications in Information Security - Mark Stamp

Discover New Methods for Dealing with High-Dimensional DataA sparse statistical model has only a small number of nonzero parameters or weights; therefore, it is much easier to estimate and interpret than a dense model. Statistical Learning with Sparsity: The Lasso and Generalizations presents methods that exploit sparsity to help recover the underlying signal in a set of data.Top experts in this rapidly evolving field, the authors describe the lasso for linear regression and a simple coordinate descent algorithm for its computation. They discuss the application of â„“1 penalties to generalized linear models and support vector machines, cover generalized penalties such as the elastic net and group lasso, and review numerical methods for optimization. They also present statistical inference methods for fitted (lasso) models, including the bootstrap, Bayesian methods, and recently developed approaches. In addition, the book examines matrix decomposition, sparse multivariate analysis, graphical models, and compressed sensing. It concludes with a survey of theoretical results for the lasso.In this age of big data, the number of features measured on a person or object can be large and might be larger than the number of observations. This book shows how the sparsity assumption allows us to tackle these problems and extract ... Unknown localization key: "more"

Objev podobné jako Statistical Learning with Sparsity - Martin Wainwright, Trevor Hastie, Robert Tibshirani

This new edition of the market-leading textbook by Paul Burns offers an unrivalled holistic introduction to the field of entrepreneurship and valuable guidance for budding entrepreneurs looking to launch their own small business.Drawing on his decades of academic and entrepreneurial experience, the author takes you on a journey through the business life-cycle, from the early stages of start-up, through progressive growth, to the confident strides of a mature business. Combining cutting-edge theory with fresh global examples and lessons from real-life business practice, this accessible and explorative textbook will encourage you to develop the knowledge and skills needed to navigate the challenges faced by today’s entrepreneurs.Entrepreneurship and Small Business will help you to:- Learn what makes entrepreneurs tick with brand new Get into the Mindset video interviews and an exploration of entrepreneuial character traits- Seamlessly incorporate multimedia content into your learning with the new Digital Links platform accessed via your smart device- Understand how worldwide events can impact small businesses through incisive analysis of the effects of the COVID-19 pandemic- Grasp how entrepreneurship differs around the globe, with over 100 Case Insights and new examples from a diverse range of countries and industries- Ensure your understanding of the entrepreneurial landscape is ... Unknown localization key: "more"

Objev podobné jako Entrepreneurship and Small Business - Paul Burns

John D. Burns, bestselling author of The Last Hillwalker, rediscovers Scotland’s mountains, bothies and wildlife in the stormiest months. Wild Winter is a reminder of the wonder of nature and the importance of caring for our environment. As he travels through the Highlands, John finds adventure, humour and a deep connection with this wild land.

Objev podobné jako Wild Winter - John D. Burns

Effective teaching is effective teaching, no matter where it occursThe pandemic teaching of mid-2020 was not really distance learning, but rather crisis teaching. But starting now, teachers have the opportunity to prepare for distance learning with purpose and intent—using what works best to accelerate students’ learning all the while maintaining an indelible focus on equity.Harnessing the insights and experience of renowned educators Douglas Fisher, Nancy Frey, and John Hattie, The Distance Learning Playbook applies the wisdom and evidence of VISIBLE LEARNING® research to understand what works best with distance learning. Spanning topics from teacher-student relationships, teacher credibility and clarity, instructional design, assessments, and grading, this comprehensive playbook details the research- and evidence-based strategies teachers can mobilize to deliver high- impact learning in an online, virtual, and distributed environment.This powerful guide includes: Learning Intentions and Success Criteria for each module to track your own learning and model evidence-based teacher practices for meaningful learning A diversity of instructional approaches, including direct instruction, peer learning, and independent work that foster student self-regulation and move learning to deep and transfer levels Discussion of equity challenges associated with distance learning, along with examples of how teachers can work to ensure that equity gains that have ... Unknown localization key: "more"

Objev podobné jako The Distance Learning Playbook, Grades K-12 - John Hattie, Douglas Fisher, Nancy Frey

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 facts—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. ... Unknown localization key: "more"

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

On publication in 2009 John Hattie’s Visible Learning presented the biggest ever collection of research into what actually work in schools to improve children’s learning. Not what was fashionable, not what political and educational vested interests wanted to champion, but what actually produced the best results in terms of improving learning and educational outcomes. It became an instant bestseller and was described by the TES as revealing education’s ‘holy grail’. Now in this latest book, John Hattie has joined forces with cognitive psychologist Greg Yates to build on the original data and legacy of the Visible Learning project, showing how it’s underlying ideas and the cutting edge of cognitive science can form a powerful and complimentary framework for shaping learning in the classroom and beyond.Visible Learning and the Science of How We Learn explains the major principles and strategies of learning, outlining why it can be so hard sometimes, and yet easy on other occasions. Aimed at teachers and students, it is written in an accessible and engaging style and can be read cover to cover, or used on a chapter-by-chapter basis for essay writing or staff development. The book is structured in three parts – ‘learning within classrooms’, ‘learning ... Unknown localization key: "more"

Objev podobné jako Visible Learning and the Science of How We Learn - John Hattie, Gregory C. R. Yates

Effective school leadership is effective leadership, regardless of where it occurs In March 2020, there was no manual for leading schools and school systems during a pandemic. School leaders had to figure things out as the crisis unfolded. But starting now, leaders have the opportunity to prepare for leading schools through distance learning with purpose and intent—using what works best to accelerate students’ learning all the while maintaining an indelible focus on equity. Harnessing the insights and experience of renowned educators Douglas Fisher, Nancy Frey, and John Hattie, The Distance Learning Playbook for School Leaders applies the wisdom and evidence of the VISIBLE LEARNING® research to understand what works best. Spanning topics from school climate at a distance, leader credibility, care for self and colleagues, instructional leadership teams, stakeholder advisory groups, and virtual visibility, this comprehensive playbook details the research- and evidence-based strategies school leaders can mobilize to lead the delivery of high-impact learning in an online, virtual, and distributed environment. This powerful guide includes: Actionable insights and hands-on steps for each module to help school leaders realize the evidence-based leadership practices that result in meaningful learning in a distance environment Discussion of equity challenges associated with distance learning, along ... Unknown localization key: "more"

Objev podobné jako The Distance Learning Playbook for School Leaders - John Hattie, Douglas Fisher, Nancy Frey, Dominique Smith

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 ... Unknown localization key: "more"

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 ... Unknown localization key: "more"

Objev podobné jako Machine Learning Algorithms in Depth - Vadim Smolyakov

MACHINE LEARNING FOR BUSINESS ANALYTICS Machine learning —also known as data mining or data analytics— 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 ... Unknown localization key: "more"

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

Since its first edition, An Introduction to Theories of Learning has provided a uniquely sweeping review of the major learning theories from the 20th century that profoundly influenced the field of psychology. In this tenth edition, the authors present further experimental evidence that tests many of the fundamental ideas presented in these classic theories, as well as explore many of the advances in psychological science and neuroscience that have yielded greater insight into the processes that underlie learning in human beings and animals. The four main goals of this text are to define learning and to show how the learning process is studied (Chapters 1 and 2), to place learning theory in historical perspective (Chapter 3), and to present essential features of the major theories of learning with implications for educational practices (Chapters 4 through 16). The authors retained the best features of earlier editions while making revisions that reflect current research and scholarship, including coverage of active learning and the testing effect, information for problem solving in ravens, data illustrating the neurobiological basis of the cognitive map and spatial learning, new research on brain plasticity and its role in learning as well as the impact of poverty on brain ... Unknown localization key: "more"

Objev podobné jako An Introduction to Theories of Learning - Julio J. Ramirez, Matthew H. Olson

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

Make learning visible in the early years   Early childhood is a uniquely sensitive time, when young learners are rapidly developing across multiple domains, including language and literacy, mathematics, and motor skills. Knowing which teaching strategies work best and when can have a significant impact on a child’s development and future success. Visible Learning in Early Childhood investigates the critical years between ages 3 and 6 and, backed by evidence from the Visible Learning® research, explores seven core strategies for learning success: working together as evaluators, setting high expectations, measuring learning with explicit success criteria, establishing developmentally appropriate levels of learning, viewing mistakes as opportunities, continually seeking feedback, and balancing surface, deep, and transfer learning. The authors unpack the symbiotic relationship between these seven tenets through Authentic examples of diverse learners and settings Voices of master teachers from the US, UK, and Australia Multiple assessment and differentiation strategies Multidisciplinary approaches depicting mathematics, literacy, art and music, social-emotional learning, and more Using the Visible Learning research, teachers partner with children to encourage high expectations, developmentally appropriate practices, the right level of challenge, and a focus on explicit success criteria. Get started today and watch your young learners thrive!

Objev podobné jako Visible Learning in Early Childhood - John Hattie, John T. Almarode, Kateri Thunder

Many machine learning problems are too complex to be resolved by a single model or algorithm. Ensemble machine learning trains a group of diverse machine learning models to work together to solve a problem. By aggregating their output, these ensemble models can flexibly deliver rich and accurate results. Ensemble Methods for Machine Learning is a guide to ensemble methods with proven records in data science competitions and real world applications. Learning from hands-on case studies, you''ll develop an under-the-hood understanding of foundational ensemble learning algorithms to deliver accurate, performant models. About the Technology Ensemble machine learning lets you make robust predictions without needing the huge datasets and processing power demanded by deep learning. It sets multiple models to work on solving a problem, combining their results for better performance than a single model working alone. This "wisdom of crowds" approach distils information from several models into a set of highly accurate results.

Objev podobné jako Ensemble Methods for Machine Learning - Gautam Kunapuli