generative deep learning david foster

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

In this rare peak into the personal life of the author of numerous bestselling novels, gain an understanding of David Foster Wallace and how he became the man that he was.Only once did David Foster Wallace give a public talk on his views on life, during a commencement address given in 2005 at Kenyon College. The speech is reprinted for the first time in book form in This is Water. How does one keep from going through their comfortable, prosperous adult life unconsciously? How do we get ourselves out of the foreground of our thoughts and achieve compassion? The speech captures Wallace s electric intellect as well as his grace in attention to others. After his death, it became a treasured piece of writing reprinted in The Wall Street Journal and the London Times, commented on endlessly in blogs, and emailed from friend to friend.Writing with his one-of-a-kind blend of causal humor, exacting intellect, and practical philosophy, David Foster Wallace probes the challenges of daily living and offers advice that renews us with every reading.

Objev podobné jako This Is Water - David Foster Wallace

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

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

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

Svůj poslední soubor povídek Zapomnění psal David Foster Wallace paralelně s již nedokončeným románem Bledý král. Kniha vyšla roku 2004. Témata osobní identity a možností porozumění i sebeporozumění se ve Wallaceových textech prolínají s nejsoučasnějšími technikami ovlivňování a vnější prezentace a kladou - nevyslovenou, snad i nevyslovitelnou? - otázku, na co jsme vlastně zapomněli. David Foster Wallace (1962-2008) patřil k nejoriginálnějším anglicky píšícím autorům přelomu tisíciletí. Proslul především románem Nekonečný žert z roku 1996. Prvním českým překladem byly Krátké rozhovory s odpornými muži, které Rubato vydalo v roce 2018.

Objev podobné jako Zapomnění - David Foster Wallace

Do lobsters feel pain? Did Franz Kafka have a sick sense of humour? What is John Updike s deal anyway? And who won the Adult Video News Female Performer of the Year Award the same year Gwyneth Paltrow won her Oscar? David Foster Wallace answers these questions and more in his new book of hilarious non-fiction. For this collection, David Foster Wallace immerses himself in the three-ring circus that is the presidential race in order to document one of the most vicious campaigns in recent history. Later he strolls from booth to booth at a lobster festival in Maine and risks life and limb to get to the bottom of the lobster question.Then he wheedles his way into an L.A. radio studio, armed with tubs of chicken, to get the behind-the-scenes view of a conservative talkshow featuring a host with an unnatural penchant for clothing that only looks good on the radio. In what is sure to be a much-talked-about exploration of distinctly modern subjects, one of the sharpest minds of our time delves into some of life s most delicious topics.

Objev podobné jako Consider The Lobster - David Foster Wallace

The Pale King is David Foster Wallace s final novel - a testament to his enduring brilliance The Internal Revenue Service Regional Examination Centre in Peoria, Illinois, 1985. Here the minutaie of a million daily lives are totted up, audited and accounted for. Here the workers fight a never-ending war against the urgency of their own boredom. Here then, squeezed between the trivial and the quotidian, lies all human life. And this is David Foster Wallace s towering, brilliant, hilarious and deeply moving final novel.

Objev podobné jako The Pale King - David Foster Wallace

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

In his startling and singular new short story collection, David Foster Wallace nudges at the boundaries of fiction with inimitable wit and seductive intelligence. Among the stories are The Depressed Person , a dazzling and blackly humorous portrayal of a woman s mental state; Adult World , which reveals a woman s agonised consideration of her confusing sexual relationship with her husband; and Brief Interviews with Hideous Men , a dark, hilarious series of portraits of men whose fear of women renders them grotesque. Wallace s stories present a world where the bizarre and the banal are interwoven and where hideous men appear in many different guises. Thought-provoking and playful, this collection confirms David Foster Wallace as one of the most imaginative young writers around. Wallace delights in leftfield observation, mining the ironic, the surprising and the illuminating from every situation. His new collection will delight his growing number of fans, and provide a perfect introduction for new readers.

Objev podobné jako Brief Interviews With Hideous Men - David Foster Wallace

A visionary, a craftsman, a comedian... he s in a different time-space continuum from the rest of us. Goddam him Zadie Smith, Guardian David Foster Wallace turns the short story upside down and inside out, making the adjectives inventive , unique and original seem blasé T. Coraghessan Boyle Truly funny surreal humour San Francisco ChronicleGirl With Curious Hair is replete with the prodigious talent of David Foster Wallace and his remarkable and unsettling re-imaginations of reality. From an eerily real , almost holographic evocation of Lyndon B. Johnson, to over-televised game-show hosts and late-night comedians, to the title story, where terminal punk nihilism meets Young Republicanism, Wallace renders the incredible comprehensible, the bizarre normal, the absurd hilarious, the familiar strange.

Objev podobné jako Girl With Curious Hair - David Foster Wallace

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

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

Kniha - autor David Foster Wallace, 138 stran, anglicky, pevná bez přebalu lesklá A classic work from the late author of "Infinite Jest", this collects his 5 essays on tennis. Once a 'near-great junior tennis player' himself, he profiles Roger Federer and Tracy Austin and writes about tennis with the authority of an insider.

Objev podobné jako String Theory: David Foster Wallace on Tennis. A Library of America Special Publication (1598534807)

V Krátkých rozhovorech s odpornými muži (1999) podává David Foster Wallace zprávu o lidských bytostech zasažených úzkostí, nejistotou a osamoceností. Formálně rozmanitý soubor povídek je jakousi verbální anatomií vztahu mezi pohlavími, výpravou do světa myslí a těl prozacového národa . Titulní cyklus, který prorůstá celou knihou, má podobu přepisu rozhovorů s 18 muži, jejichž promluvy jsou formovány nepřítomností tázající osoby. Strach mužů z ženských soudů tu ústí v egománii, mizogynii a objektivizaci svého protějšku. Wallacovy prozaické útvary jsou obydleny personalizovanými postoji, s nimiž by se málokdo chtěl identifikovat, které se ale mnohým budou zdát až znepokojivě povědomé. Mluví tu přízraky, nebo skutečné osoby v nás?

Objev podobné jako Krátké rozhovory s odpornými muži - David Foster Wallace

Gathered for the first time in a deluxe collector s edition, here are David Foster Wallace s legendary writings on tennis, five tour-de-force pieces written with a competitor s insight and a fan s obsessive enthusiasm. Wallace brings his dazzling literary magic to the game he loved as he celebrates the other-worldly genius of Roger Federer; offers a wickedly witty disection of Tracy Austin s memoir; considers the artistry of Michael Joyce, a supremely disciplined athlete on the threshold of fame; resists the crush of commerce at the U.S. Open; and recalls his own career as a near-great junior player.Whiting Award-winning writer John Jeremiah Sullivan provides an introduction.

Objev podobné jako String Theory - David Foster Wallace

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

This book provides essential knowledge and skills to address all the new social work education requirements for placements and practice learning. It will help you successfully pass your compulsory social work placement whilst meeting the Professional Capabilities Framework (PCF) for Social Workers and developing their professional practice. Giving examples of the PCF plus clear exercises, strategies and tips, the book: -Introduces your students to social work in the context of contemporary reforms. -Takes you through each stage of the new placement structure explaining supervision, reflective practice and critical thinking in social work. -Addresses trouble shooting and problem solving on placement. -Helps you prepare for complex casework with individuals, families, groups and communities; address risk in social work; and engage with diverse groups and communities. By using this book, you⠲ll be armed with the tools you need to get the most out of your placement. David Edmondson is Senior Lecturer in Social Work at Manchester Metropolitan University

Objev podobné jako Social Work Practice Learning - David Edmondson

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

If you are going to care for someone, you must first understand them. If you re going to hire, marry, or befriend someone, you have to be able to see them. If you are going to work closely with someone, you have to be able to make them feel recognized and valued.As David Brooks observes, The older I get, the more I come to the certainty that there is one skill at the center of any healthy family, company, classroom, community or nation: the ability to see each other, to know other people, to make them feel valued, heard and understood. And yet we humans don t do this well. All around us are people who feel invisible, unseen, misunderstood. In How to Know a Person, Brooks sets out to help us to do better, posing questions that are essential for all of us.Driven by his trademark sense of curiosity, Brooks draws from the fields of psychology and neuroscience, and from the worlds of theatre, history, and education, to present a welcoming, hopeful, integrated approach to human connection. How to Know a Person helps readers become more understanding and considerate towards others; it helps readers find the joy that comes from being seen. Along the way it offers a possible remedy for a society that is riven by fragmentation, hostility, and misperception.The act of seeing another person, Brooks argues, is a profoundly creative act: How can we look somebody in the eye and see something large in them, and in turn, see something larger in ourselves? How to Know a Person is for anyone searching for connection, seeking to understand and yearning to be understood.

Objev podobné jako How To Know a Person: The Art of Seeing Others Deeply and Being Deeply Seen - David Brooks

A Stelton Norman Foster cukřenka egy 200 ml-es fehér porcelán tál, amelyet a világhírű brit építész tervezett. Egyszerű szobrászi formáit finom geometriai elemekkel kombinálja, és cukor mellett desszertek vagy reggeli tárolására is alkalmas. Kényelmesen megfogható, és mindennapi használat mellett ünnepi asztaldíszként is funkcionál.

• Norman Foster brit építész ikonikus designja
• Többfunkciós használat: cukor, desszert, reggeli
• Kényelmes fogású, kifinomult geometriai formák
• Minőségi porcelán, mindennapi és ünnepi alkalmakra egyaránt

Objev podobné jako Cukřenka NORMAN FOSTER 200 ml, bílá, porcelán, Stelton

A Stelton Norman Foster világosszürke sómalma 13 cm magas, PA66 műanyagból készült. CrushGrind kerámia őrlő mechanizmussal rendelkezik, amely 25 év garanciát biztosít, és beállítható finom vagy durva őrlésre. A design megakadályozza a só szóródását, és kiegészíti a Norman Foster antracit borsmalmot.

• Norman Foster világhírű építész tervezte, ikonikus design
• 25 év garanciával rendelkező CrushGrind kerámia őrlő mechanizmus
• Extrémül tartós PA66 műanyag felépítés
• Beállítható finom vagy durva őrlés, szóródásgátló kialakítás

Objev podobné jako Mlýnek na sůl NORMAN FOSTER 13 cm, světle šedá, plast, Stelton

Ez a 1 literes Stelton karafa rozsdamentes acélból készült, PVD bevonattal és Norman Foster dizájnjával. A belső arany bevonat elegáns megjelenést kölcsönöz, míg a dugó biztonságos tárolást és szállítást tesz lehetővé. Méretei 10,5 x 27 cm, ideális asztali dekorációként vagy modern bárkiegészítőként.

• Norman Foster világhírű építész exkluzív dizájnja
• PVD bevonat a tartósságért és elegáns megjelenésért
• Hűtőtartó képesség a hosszabb ideig hideg italokért
• Gyakorlatos dugó a véletlen kiöntés megelőzésére

Objev podobné jako Karafa na vodu NORMAN FOSTER 1 l, stříbrná / zlatá, nerezová ocel, Stelton

A Norman Foster által tervezett dekoratív tálca aszimmetrikus formájú, nerez acélból készült, PVD bevonattal. 46 cm átmérőjű, arany hátoldallal rendelkezik, és funkcionális vagy díszítő célra egyaránt alkalmas. Modern esztétikája és tartóssága kiemelkedő.

• Aszimmetrikus forma, amely funkcionális és dekoratív elemként egyaránt szolgál.
• PVD bevonattal ellátott nerez acél, amely tartósságot és elegáns megjelenést biztosít.
• Norman Foster brit építész által tervezett, egyedi geometriai formákkal.

Objev podobné jako Dekorativní podnos NORMAN FOSTER 46 cm, stříbrná / zlatá, nerezová ocel, Stelton

A Stelton Norman Foster tál egy 36 cm átmérőjű, aszimmetrikus formájú nerezacél edény, amely PVD bevonattal rendelkezik. A tál előlapja ezüst, hátulja arany színű, így dekoratív központi darabként vagy gyümölcs, csokoládé tárolására egyaránt alkalmas. A design a brit építész, Norman Foster nevéhez fűződik, és modern esztétikát képvisel.

• Norman Foster brit építész ikonikus aszimmetrikus designja
• PVD bevonat a tartósság és a korrózióállóság érdekében
• Elegáns, kétoldalas megjelenés: ezüst előlap és arany háttal

Objev podobné jako Mísa na ovoce NORMAN FOSTER 36 cm, stříbrná / zlatá, nerezová ocel, Stelton

Ez a Stelton francia press kávéfőző Norman Foster tervezte, és 1 literes kapacitású. Rozsdamentes acélból készült, és kettős funkciót tölt be: kávéfőzőként és hőszigetelt szervírozó kancsóként egyaránt használható. Kiváló hőtartó képessége akár négy óráig is melegen tartja a kávét.

• Norman Foster brit építész által tervezett ikonikus design
• Kettős funkció: francia press kávéfőző és hőszigetelt szervírozó kancsó
• Rozsdamentes acél konstrukció, amely akár 4 óráig is melegen tartja a kávét

Objev podobné jako French press kávovar NORMAN FOSTER 1 l, stříbrná, nerezová ocel, Stelton

A Norman Foster tervezte 1 literes vakuumos kancsó boroszilikát üveg izoláló bélésével órákig melegen vagy hidegen tartja a kávét, teát vagy egyéb italokat. BPA-mentes műanyagból készült, könnyen tisztítható, és kiválóan alkalmas mindennapi használatra otthon vagy piknikeken. Modern, tisztán formált designja díszíti az asztalt, és kényelmes kezelhetőséget biztosít a széles kiöntő szájának és nagy fogójának köszönhetően.

• Boroszilikát üveg izoláló bélés órákig melegen vagy hidegen tartja az italokat
• Norman Foster brit építész ikonikus, modern designja
• BPA-mentes műanyag, könnyen tisztítható és karbantartható
• Széles kiöntő száj és nagy fogó könnyű kezelhetőséget biztosít

Objev podobné jako Vakuový džbán NORMAN FOSTER 1 l, světle šedá, plast, Stelton

Ez a 1 literes teáskanna a francia press módszerrel készíti a teát, és kiváló hőszigetelésének köszönhetően akár négy órán át is melegen tartja. A világhírű építész, Norman Foster tervezte, prémium rozsdamentes acélból készült, és integrált szűrővel rendelkezik. Kétfunkciós kialakítása lehetővé teszi, hogy teakészítésre és elegáns asztali szervírozásra is használható legyen.

• Norman Foster világhírű építész exkluzív designja
• Kiváló hőszigetelés: akár 4 órán át melegen tartja a teát
• Prémium anyagok: rozsdamentes acél és elegáns arany belső felület
• Kétfunkciós: francia press teáskanna és szervírozó kancsó egyben

Objev podobné jako French press čajovar NORMAN FOSTER 1 l, stříbrná, nerezová ocel, Stelton

A Stelton Norman Foster 1 literes vakuumkancsó antracit színben készült, műanyag, üveg és szilikon anyagokból. Hőszigetelő belső rétege órákig melegen vagy hidegen tartja a kávét, teát vagy egyéb italokat. Kialakítása praktikus, könnyen kezelhető és karbantartható.

• Norman Foster brit építész által tervezett ikonikus design
• Borszilikát üveg hőszigetelő bélés hosszú órákig melegen/ hidegen tartja italokat
• BPA-mentes műanyag és kényelmes fogantyú biztonságos használatot biztosít
• Könnyen tisztítható, mindennapi használatra és piknikekre egyaránt ideális

Objev podobné jako Vakuový džbán NORMAN FOSTER 1 l, antracitová, plast, Stelton

A Stelton Norman Foster 200 ml-es vízospohárkészlet 2 darab tiszta üvegpoharat tartalmaz, amelyeket a világhírű brit építész tervezett. A pohárk széles alappal rendelkezik a stabilitás érdekében, és kényelmesen megfogható. Mindennapi használatra és ünnepi alkalmakra egyaránt alkalmas.

• Norman Foster brit építész exkluzív tervezése
• Stabil széles alappal és kényelmes fogással
• Egyszerű szobrászi formák és finom geometria

Objev podobné jako Sklenice na vodu NORMAN FOSTER 200 ml, sada 2 ks, čirá, sklo, Stelton

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

THE FASCINATING SUNDAY TIMES TOP TEN BESTSELLERAssaults. Riots. Cell fires. Medical emergencies. Understaffed wings. Suicides. Hooch. Weapons. It s all in a week s work at HMP Parkhurst.After 28 years working as a prison officer, with 22 years at HMP Parkhurst, once one of Britain s most high security prisons, David Berridge has had to deal with it all: serial killers and gangsters, terrorists and sex offenders, psychopaths and addicts. InsideParkhurst is his raw, uncompromising look at what really goes on behind the massive walls and menacing gates. Thrown in at the deep end, David quickly had to work out how to deal with the most cunning and volatile of prisoners, and learn how to avoid their many scams. He has been assaulted and abused; he has tackled cell fires and attempted suicides, riots and dirty protests; he has helped to foil escaped plans, talked inmates down from rooftop protests, witnessed prisoners setting fire to themselves, and prevented prisoners from attempting to murder other prisoners. And now he takes us inside this secret world for the first time.With this searingly honest account he guides us around the wings, the segregation unit, the hospital and the exercise yard, and gives vivid portraits of the drug taking, the hooch making, the constant and irrepressible violence, and the extraordinary lengths our prison officers go to everyday. Divided into three parts - the first from David s early years on the wings, the second the middle of his career, and the third his disillusioned later years - David will take readers into the heart of life inside and shine a light on the escalating violence and the impact the government cuts are having on the wings.Both horrifying and hilarious, David s diaries are guaranteed to shock and entertain in equal measure.

Objev podobné jako Inside Parkhurst - David Berridge

How are David Lynchâ ™s films as much in dialogue with literary and musical traditions as they are cinematic ones? By interrogating this question, David Lynchâ ™s American Dreamscape broadens the interpretive horizons of Lynchâ ™s filmography, calling for a new approach to Lynchâ ™s films that goes beyond cinema and visual art to explore how Lynchâ ™s work engages with literary and musical works that have shaped the American imagination. As much as Lynch stands as a singular artistic voice, his work arises from and taps into the cultural zeitgeist in a way that illuminates not only his approach to creativity but also the way works interact with each other in an age of mass media. From childrenâ ™s literature to teen tragedy ballads, Nathanael West and Cormac McCarthy to folk music and mixtapes, David Lynchâ ™s American Dreamscape investigates the cultural frequencies Lynchâ ™s films tune into and positions Lynchâ ™s work as a conduit for American popular culture, a medium or channel through which the subconscious of American life finds its way into full view.The book expands upon this approach by discussing how artists such as David Foster Wallace and Lana Del Rey graft Lynchâ ™s affiliative, cinematic sensibility onto their own projects. Reading their work as intertextual engagements with Lynchâ ™s films further illustrates the versatile interactions among creators and audiences to generate more works, readers, and readings.

Objev podobné jako David Lynchâ

Discover the Good Life as you learn from the wise voices of the past.We ve lost ourselves. Disconnected from the past and uncertain about the future, we are anxious about what our lives will be and troubled by a nagging sense of meaninglessness. Adrift in the world, many Christians have their identity completely wrapped up in work, and their definition of the good life is financial success. Fewer of are staying committed to the Christian faith, finding it difficult to reconcile their experience with their longings and desires. With so much uncertainty, where can we find a true vision of the Good Life ?Learning the Good Life speaks to this malaise with a curated collection of voices from the past, inviting Christians into an ages-old dialogue with some of history s wisest and most reflective minds. Featuring thought-provoking writings from a diverse lineup of over 35 writers and thinkers:From the classic—including Confucius, Augustine, Sor Juana Inés de la Cruz, Henry David Thoreau, and Frederick Douglass;To the modern—including W.E.B. DuBois, Flannery O Connor, T.S. Eliot, and Simone Weil;To the contemporary—including Wendell Berry, David Foster Wallace, and Marilynne Robinson.Together these sages, writers, philosophers, and poets address important issues such as virtue, beauty, community, wonder, suffering, and meaning.Each of these texts are introduced by experts from a variety of Christian colleges and universities to help provide a richer narrative in which Christians can participate. Each text is also accompanied by discussion questions to provoke further thought and contemplation and to facilitate discussion when used in groups.Learning the Good Life is ideal for any Christian seeking a deeper connection to the wisdom of the past and wanting a more cohesive vision of the good life. Though not all these writers were themselves Christians, they all have a message for you. All of them are calling you to die to yourself, to your habits of indulgence, to your pride and ambition—and to dedicate your time to learning, thinking, and loving.

Objev podobné jako Learning the Good Life - Jacob Stratman, Jessica Hooten Wilson

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