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Author: Ian Goodfellow
Publisher: MIT Press
ISBN: 0262337371
Category : Computers
Languages : en
Pages : 801
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Book Description
An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. “Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.” —Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models. Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.
Author: Ian Goodfellow
Publisher: MIT Press
ISBN: 0262337371
Category : Computers
Languages : en
Pages : 801
Get Book Here
Book Description
An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. “Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.” —Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models. Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.
Author: Talk To Me In Korean
Publisher: Talk To Me In Korean
ISBN:
Category : Foreign Language Study
Languages : en
Pages : 496
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Book Description
Learn your first 500 Korean words and thousands of related words and expressions that you can start using right away in your everyday conversations in Korean!
Author: Joi Barrios
Publisher: Tuttle Publishing
ISBN: 1462910394
Category : Foreign Language Study
Languages : en
Pages : 443
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Book Description
This is a straightforward and user-friendly guide to the Tagalog language. Tagalog for Beginners is the book to help you learn Tagalog (Filipino) on your own, efficiently and accurately--whether you're traveling to the Philippines for a vacation or a business trip, or you have ties to the sizeable Tagalog-speaking community in the U.S., or you're merely a language lover. From the fascinating history of Philippines' language to how you speak it, join skilled teacher Barrios on a guided introduction--with a practical focus. After journeying through the carefully-paced explanations, conversations, cultural info, and activities in Tagalog for Beginners, learners will be able to use Tagalog (Filipino) in a wide range of natural situations. From shopping for food to asking directions, from telling time to expressing how you feel, this book gives you the communication skills you need. The downloadable audio helps reinforce pronunciation and improve listening comprehension. Helpful suggestions guide heritage learners (those of Filipino descent but born outside the Philippines) on how to use the book most effectively for their needs. Key features include:: Accompanying downloadable audio. Realistic dialogues to bring the language to life. Activities and exercises to help you read, write, speak and understand. Notes on the Tagalog language and history. A specific section guides native (heritage) learners and instructors on how to use the book most effectively for their needs.
Author: Collins Dictionaries
Publisher: HarperCollins UK
ISBN: 0008180709
Category : Foreign Language Study
Languages : en
Pages : 702
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Book Description
A handy 3-in-1 French study book: grammar, verbs and vocabulary in one volume, ideal for beginners who need a clear and easy-to-understand French reference and revision guide.
Author: Cal Newport
Publisher: Crown
ISBN: 0767922719
Category : Study Aids
Languages : en
Pages : 226
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Book Description
Looking to jumpstart your GPA? Most college students believe that straight A’s can be achieved only through cramming and painful all-nighters at the library. But Cal Newport knows that real straight-A students don’t study harder—they study smarter. A breakthrough approach to acing academic assignments, from quizzes and exams to essays and papers, How to Become a Straight-A Student reveals for the first time the proven study secrets of real straight-A students across the country and weaves them into a simple, practical system that anyone can master. You will learn how to: • Streamline and maximize your study time • Conquer procrastination • Absorb the material quickly and effectively • Know which reading assignments are critical—and which are not • Target the paper topics that wow professors • Provide A+ answers on exams • Write stellar prose without the agony A strategic blueprint for success that promises more free time, more fun, and top-tier results, How to Become a Straight-A Student is the only study guide written by students for students—with the insider knowledge and real-world methods to help you master the college system and rise to the top of the class.
Author: Jan Richardson
Publisher: Scholastic Professional
ISBN: 9781338732856
Category :
Languages : en
Pages : 240
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Book Description
In the hands of informed teachers, running records reveal the meaning-making, problem-solving strategies children are using as they process text. Richardson, Bates, and McBride provide expert analysis of sample running records and offer how-to videos that take teachers beyond calculating a simple accuracy rate to observing their students' reading behaviors--and then taking next steps to plan targeted lessons.
Author: Richard S. Sutton
Publisher: MIT Press
ISBN: 0262352702
Category : Computers
Languages : en
Pages : 549
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Book Description
The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence. Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the field's key ideas and algorithms. This second edition has been significantly expanded and updated, presenting new topics and updating coverage of other topics. Like the first edition, this second edition focuses on core online learning algorithms, with the more mathematical material set off in shaded boxes. Part I covers as much of reinforcement learning as possible without going beyond the tabular case for which exact solutions can be found. Many algorithms presented in this part are new to the second edition, including UCB, Expected Sarsa, and Double Learning. Part II extends these ideas to function approximation, with new sections on such topics as artificial neural networks and the Fourier basis, and offers expanded treatment of off-policy learning and policy-gradient methods. Part III has new chapters on reinforcement learning's relationships to psychology and neuroscience, as well as an updated case-studies chapter including AlphaGo and AlphaGo Zero, Atari game playing, and IBM Watson's wagering strategy. The final chapter discusses the future societal impacts of reinforcement learning.
Author: Barbara Oakley, PhD
Publisher: Penguin
ISBN: 052550446X
Category : Juvenile Nonfiction
Languages : en
Pages : 258
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Book Description
A surprisingly simple way for students to master any subject--based on one of the world's most popular online courses and the bestselling book A Mind for Numbers A Mind for Numbers and its wildly popular online companion course "Learning How to Learn" have empowered more than two million learners of all ages from around the world to master subjects that they once struggled with. Fans often wish they'd discovered these learning strategies earlier and ask how they can help their kids master these skills as well. Now in this new book for kids and teens, the authors reveal how to make the most of time spent studying. We all have the tools to learn what might not seem to come naturally to us at first--the secret is to understand how the brain works so we can unlock its power. This book explains: Why sometimes letting your mind wander is an important part of the learning process How to avoid "rut think" in order to think outside the box Why having a poor memory can be a good thing The value of metaphors in developing understanding A simple, yet powerful, way to stop procrastinating Filled with illustrations, application questions, and exercises, this book makes learning easy and fun.
Author: Andrew W. Trask
Publisher: Simon and Schuster
ISBN: 163835720X
Category : Computers
Languages : en
Pages : 492
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Book Description
Summary Grokking Deep Learning teaches you to build deep learning neural networks from scratch! In his engaging style, seasoned deep learning expert Andrew Trask shows you the science under the hood, so you grok for yourself every detail of training neural networks. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Deep learning, a branch of artificial intelligence, teaches computers to learn by using neural networks, technology inspired by the human brain. Online text translation, self-driving cars, personalized product recommendations, and virtual voice assistants are just a few of the exciting modern advancements possible thanks to deep learning. About the Book Grokking Deep Learning teaches you to build deep learning neural networks from scratch! In his engaging style, seasoned deep learning expert Andrew Trask shows you the science under the hood, so you grok for yourself every detail of training neural networks. Using only Python and its math-supporting library, NumPy, you'll train your own neural networks to see and understand images, translate text into different languages, and even write like Shakespeare! When you're done, you'll be fully prepared to move on to mastering deep learning frameworks. What's inside The science behind deep learning Building and training your own neural networks Privacy concepts, including federated learning Tips for continuing your pursuit of deep learning About the Reader For readers with high school-level math and intermediate programming skills. About the Author Andrew Trask is a PhD student at Oxford University and a research scientist at DeepMind. Previously, Andrew was a researcher and analytics product manager at Digital Reasoning, where he trained the world's largest artificial neural network and helped guide the analytics roadmap for the Synthesys cognitive computing platform. Table of Contents Introducing deep learning: why you should learn it Fundamental concepts: how do machines learn? Introduction to neural prediction: forward propagation Introduction to neural learning: gradient descent Learning multiple weights at a time: generalizing gradient descent Building your first deep neural network: introduction to backpropagation How to picture neural networks: in your head and on paper Learning signal and ignoring noise:introduction to regularization and batching Modeling probabilities and nonlinearities: activation functions Neural learning about edges and corners: intro to convolutional neural networks Neural networks that understand language: king - man + woman == ? Neural networks that write like Shakespeare: recurrent layers for variable-length data Introducing automatic optimization: let's build a deep learning framework Learning to write like Shakespeare: long short-term memory Deep learning on unseen data: introducing federated learning Where to go from here: a brief guide
Author: Bruce K. Britton
Publisher: Routledge
ISBN: 1136469680
Category : Education
Languages : en
Pages : 210
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Book Description
It is surprising that there is so little research on textbooks, given their centrality to teaching and learning in elementary and secondary schools. Textbooks have become a focus of political and cultural controversy, advocating a multicultural curriculum that has sparked some vigorous protests. Research is absent in this debate; therefore, questions of legitimate knowledge, the role of textbooks, textbook design, policy selection issues, and economic issues concerning the marketplace are not part of the current debate. Without insights of research on considerate text, mentioning, illustrations and so forth, the current controversy will result in publishers responding to demands for more content not less; thus, textbooks will become compendia of information that on the surface satisfy everyone. This volume demonstrates how research on important issues relative to textbook design can advance our knowledge about what makes textbooks effective learning tools, and thus inform policymakers, publishers, and those involved in textbook selection. Representing pure and applied approaches, researchers present papers on the quality of writing, the role of questions, the role of pictures and illustrations, and the role of auxiliary materials in the design of effective textbooks. The chapters provide insight into research and its application to textbook design and improvement -- stimulating others to follow this lead.
