Author: Al Sweigart
Publisher: No Starch Press
ISBN: 1593279663
Category : Computers
Languages : en
Pages : 385
Book Description
BRIDGE THE GAP BETWEEN NOVICE AND PROFESSIONAL You've completed a basic Python programming tutorial or finished Al Sweigart's bestseller, Automate the Boring Stuff with Python. What's the next step toward becoming a capable, confident software developer? Welcome to Beyond the Basic Stuff with Python. More than a mere collection of advanced syntax and masterful tips for writing clean code, you'll learn how to advance your Python programming skills by using the command line and other professional tools like code formatters, type checkers, linters, and version control. Sweigart takes you through best practices for setting up your development environment, naming variables, and improving readability, then tackles documentation, organization and performance measurement, as well as object-oriented design and the Big-O algorithm analysis commonly used in coding interviews. The skills you learn will boost your ability to program--not just in Python but in any language. You'll learn: Coding style, and how to use Python's Black auto-formatting tool for cleaner code Common sources of bugs, and how to detect them with static analyzers How to structure the files in your code projects with the Cookiecutter template tool Functional programming techniques like lambda and higher-order functions How to profile the speed of your code with Python's built-in timeit and cProfile modules The computer science behind Big-O algorithm analysis How to make your comments and docstrings informative, and how often to write them How to create classes in object-oriented programming, and why they're used to organize code Toward the end of the book you'll read a detailed source-code breakdown of two classic command-line games, the Tower of Hanoi (a logic puzzle) and Four-in-a-Row (a two-player tile-dropping game), and a breakdown of how their code follows the book's best practices. You'll test your skills by implementing the program yourself. Of course, no single book can make you a professional software developer. But Beyond the Basic Stuff with Python will get you further down that path and make you a better programmer, as you learn to write readable code that's easy to debug and perfectly Pythonic Requirements: Covers Python 3.6 and higher
Basics of Linear Algebra for Machine Learning
Author: Jason Brownlee
Publisher: Machine Learning Mastery
ISBN:
Category : Computers
Languages : en
Pages : 211
Book Description
Linear algebra is a pillar of machine learning. You cannot develop a deep understanding and application of machine learning without it. In this laser-focused Ebook, you will finally cut through the equations, Greek letters, and confusion, and discover the topics in linear algebra that you need to know. Using clear explanations, standard Python libraries, and step-by-step tutorial lessons, you will discover what linear algebra is, the importance of linear algebra to machine learning, vector, and matrix operations, matrix factorization, principal component analysis, and much more.
Publisher: Machine Learning Mastery
ISBN:
Category : Computers
Languages : en
Pages : 211
Book Description
Linear algebra is a pillar of machine learning. You cannot develop a deep understanding and application of machine learning without it. In this laser-focused Ebook, you will finally cut through the equations, Greek letters, and confusion, and discover the topics in linear algebra that you need to know. Using clear explanations, standard Python libraries, and step-by-step tutorial lessons, you will discover what linear algebra is, the importance of linear algebra to machine learning, vector, and matrix operations, matrix factorization, principal component analysis, and much more.
Deep Learning
Author: Ian Goodfellow
Publisher: MIT Press
ISBN: 0262337371
Category : Computers
Languages : en
Pages : 801
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.
Publisher: MIT Press
ISBN: 0262337371
Category : Computers
Languages : en
Pages : 801
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.
Learning How to Learn
Author: Barbara Oakley, PhD
Publisher: Penguin
ISBN: 052550446X
Category : Juvenile Nonfiction
Languages : en
Pages : 258
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.
Publisher: Penguin
ISBN: 052550446X
Category : Juvenile Nonfiction
Languages : en
Pages : 258
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.
Deep Learning
Author: Andrew Glassner
Publisher: No Starch Press
ISBN: 1718500734
Category : Computers
Languages : en
Pages : 1315
Book Description
A richly-illustrated, full-color introduction to deep learning that offers visual and conceptual explanations instead of equations. You'll learn how to use key deep learning algorithms without the need for complex math. Ever since computers began beating us at chess, they've been getting better at a wide range of human activities, from writing songs and generating news articles to helping doctors provide healthcare. Deep learning is the source of many of these breakthroughs, and its remarkable ability to find patterns hiding in data has made it the fastest growing field in artificial intelligence (AI). Digital assistants on our phones use deep learning to understand and respond intelligently to voice commands; automotive systems use it to safely navigate road hazards; online platforms use it to deliver personalized suggestions for movies and books - the possibilities are endless. Deep Learning: A Visual Approach is for anyone who wants to understand this fascinating field in depth, but without any of the advanced math and programming usually required to grasp its internals. If you want to know how these tools work, and use them yourself, the answers are all within these pages. And, if you're ready to write your own programs, there are also plenty of supplemental Python notebooks in the accompanying Github repository to get you going. The book's conversational style, extensive color illustrations, illuminating analogies, and real-world examples expertly explain the key concepts in deep learning, including: • How text generators create novel stories and articles • How deep learning systems learn to play and win at human games • How image classification systems identify objects or people in a photo • How to think about probabilities in a way that's useful to everyday life • How to use the machine learning techniques that form the core of modern AI Intellectual adventurers of all kinds can use the powerful ideas covered in Deep Learning: A Visual Approach to build intelligent systems that help us better understand the world and everyone who lives in it. It's the future of AI, and this book allows you to fully envision it. Full Color Illustrations
Publisher: No Starch Press
ISBN: 1718500734
Category : Computers
Languages : en
Pages : 1315
Book Description
A richly-illustrated, full-color introduction to deep learning that offers visual and conceptual explanations instead of equations. You'll learn how to use key deep learning algorithms without the need for complex math. Ever since computers began beating us at chess, they've been getting better at a wide range of human activities, from writing songs and generating news articles to helping doctors provide healthcare. Deep learning is the source of many of these breakthroughs, and its remarkable ability to find patterns hiding in data has made it the fastest growing field in artificial intelligence (AI). Digital assistants on our phones use deep learning to understand and respond intelligently to voice commands; automotive systems use it to safely navigate road hazards; online platforms use it to deliver personalized suggestions for movies and books - the possibilities are endless. Deep Learning: A Visual Approach is for anyone who wants to understand this fascinating field in depth, but without any of the advanced math and programming usually required to grasp its internals. If you want to know how these tools work, and use them yourself, the answers are all within these pages. And, if you're ready to write your own programs, there are also plenty of supplemental Python notebooks in the accompanying Github repository to get you going. The book's conversational style, extensive color illustrations, illuminating analogies, and real-world examples expertly explain the key concepts in deep learning, including: • How text generators create novel stories and articles • How deep learning systems learn to play and win at human games • How image classification systems identify objects or people in a photo • How to think about probabilities in a way that's useful to everyday life • How to use the machine learning techniques that form the core of modern AI Intellectual adventurers of all kinds can use the powerful ideas covered in Deep Learning: A Visual Approach to build intelligent systems that help us better understand the world and everyone who lives in it. It's the future of AI, and this book allows you to fully envision it. Full Color Illustrations
Facilitating Father's Groups
Author: Haji Shearer
Publisher:
ISBN: 9780989500906
Category :
Languages : en
Pages : 256
Book Description
Facilitate Better Groups Faster! The 22 archetypes examined in Facilitating Fathers' Groups guide you through the maze of successfully leading a dynamic group experience. Facilitators of any type of group will benefit from using the archetypal approach outlined in this book. The focus of the text, however, is on facilitating fathers' groups so more men are inspired to actively parent and the pain from father absence is diminished. Facilitating Fathers' Groups helps you create fun, learning environments that empower participants to make the positive change that they desire in their lives. Fathers' groups are especially crucial to support men in the many communities where father absence is epidemic. The time has come for men to gather and inspire one another to become more involved, loving fathers. This book shows you how to make that happen!
Publisher:
ISBN: 9780989500906
Category :
Languages : en
Pages : 256
Book Description
Facilitate Better Groups Faster! The 22 archetypes examined in Facilitating Fathers' Groups guide you through the maze of successfully leading a dynamic group experience. Facilitators of any type of group will benefit from using the archetypal approach outlined in this book. The focus of the text, however, is on facilitating fathers' groups so more men are inspired to actively parent and the pain from father absence is diminished. Facilitating Fathers' Groups helps you create fun, learning environments that empower participants to make the positive change that they desire in their lives. Fathers' groups are especially crucial to support men in the many communities where father absence is epidemic. The time has come for men to gather and inspire one another to become more involved, loving fathers. This book shows you how to make that happen!
Education
Author: Kay Wood
Publisher: Routledge
ISBN: 0415589541
Category : Education
Languages : en
Pages : 193
Book Description
This is a lively and engaging introduction to education as an academic subject, taking into account both theory and practice. Covering the schooling system, the nature of knowledge and methods of teaching, it analyses the viewpoints of both teachers and pupils.
Publisher: Routledge
ISBN: 0415589541
Category : Education
Languages : en
Pages : 193
Book Description
This is a lively and engaging introduction to education as an academic subject, taking into account both theory and practice. Covering the schooling system, the nature of knowledge and methods of teaching, it analyses the viewpoints of both teachers and pupils.
Guide to Deep Learning Basics
Author: Sandro Skansi
Publisher: Springer Nature
ISBN: 3030375919
Category : Computers
Languages : en
Pages : 144
Book Description
This stimulating text/reference presents a philosophical exploration of the conceptual foundations of deep learning, presenting enlightening perspectives that encompass such diverse disciplines as computer science, mathematics, logic, psychology, and cognitive science. The text also highlights select topics from the fascinating history of this exciting field, including the pioneering work of Rudolf Carnap, Warren McCulloch, Walter Pitts, Bulcsú László, and Geoffrey Hinton. Topics and features: Provides a brief history of mathematical logic, and discusses the critical role of philosophy, psychology, and neuroscience in the history of AI Presents a philosophical case for the use of fuzzy logic approaches in AI Investigates the similarities and differences between the Word2vec word embedding algorithm, and the ideas of Wittgenstein and Firth on linguistics Examines how developments in machine learning provide insights into the philosophical challenge of justifying inductive inferences Debates, with reference to philosophical anthropology, whether an advanced general artificial intelligence might be considered as a living being Investigates the issue of computational complexity through deep-learning strategies for understanding AI-complete problems and developing strong AI Explores philosophical questions at the intersection of AI and transhumanism This inspirational volume will rekindle a passion for deep learning in those already experienced in coding and studying this discipline, and provide a philosophical big-picture perspective for those new to the field.
Publisher: Springer Nature
ISBN: 3030375919
Category : Computers
Languages : en
Pages : 144
Book Description
This stimulating text/reference presents a philosophical exploration of the conceptual foundations of deep learning, presenting enlightening perspectives that encompass such diverse disciplines as computer science, mathematics, logic, psychology, and cognitive science. The text also highlights select topics from the fascinating history of this exciting field, including the pioneering work of Rudolf Carnap, Warren McCulloch, Walter Pitts, Bulcsú László, and Geoffrey Hinton. Topics and features: Provides a brief history of mathematical logic, and discusses the critical role of philosophy, psychology, and neuroscience in the history of AI Presents a philosophical case for the use of fuzzy logic approaches in AI Investigates the similarities and differences between the Word2vec word embedding algorithm, and the ideas of Wittgenstein and Firth on linguistics Examines how developments in machine learning provide insights into the philosophical challenge of justifying inductive inferences Debates, with reference to philosophical anthropology, whether an advanced general artificial intelligence might be considered as a living being Investigates the issue of computational complexity through deep-learning strategies for understanding AI-complete problems and developing strong AI Explores philosophical questions at the intersection of AI and transhumanism This inspirational volume will rekindle a passion for deep learning in those already experienced in coding and studying this discipline, and provide a philosophical big-picture perspective for those new to the field.
Basics of Drawing
Author: Leonardo Pereznieto
Publisher: Union Square & Co.
ISBN: 1684620309
Category : Art
Languages : en
Pages : 146
Book Description
Popular artist Leonardo Pereznieto—whose instructional YouTube videos have earned him millions of views and a devoted fan base—teaches beginners the fundamentals of traditional drawing. In his first book “You Can Draw!” Leonardo Pereznieto helped artists recreate the realistic surfaces and textures that make his own work so popular. Now he’s going back to the very beginning to teach them the basics of drawing, covering first exercises, fundamental techniques, light and shading, composition, and perspective, and more. Loaded with information on materials, a glossary of essential terminology, and hundreds of illustrations, this illuminating guide includes such projects as a fall still life of fruit in a basket, with instructions on shape, shadow, and detail, as well as a cityscape, a landscape with depth of field, animals, train tracks, jewelry, and drawing with a message. Once you’ve mastered these basics, you can unleash your imagination on whatever subject you like!
Publisher: Union Square & Co.
ISBN: 1684620309
Category : Art
Languages : en
Pages : 146
Book Description
Popular artist Leonardo Pereznieto—whose instructional YouTube videos have earned him millions of views and a devoted fan base—teaches beginners the fundamentals of traditional drawing. In his first book “You Can Draw!” Leonardo Pereznieto helped artists recreate the realistic surfaces and textures that make his own work so popular. Now he’s going back to the very beginning to teach them the basics of drawing, covering first exercises, fundamental techniques, light and shading, composition, and perspective, and more. Loaded with information on materials, a glossary of essential terminology, and hundreds of illustrations, this illuminating guide includes such projects as a fall still life of fruit in a basket, with instructions on shape, shadow, and detail, as well as a cityscape, a landscape with depth of field, animals, train tracks, jewelry, and drawing with a message. Once you’ve mastered these basics, you can unleash your imagination on whatever subject you like!
Basics of Language for Language Learners, 2nd Edition
Author: Peter W. Culicover
Publisher:
ISBN: 9780814254431
Category : Foreign Language Study
Languages : en
Pages : 264
Book Description
Basics of Language for Language Learners, 2nd edition, by Peter W. Culicover and Elizabeth V. Hume, systematically explores all the aspects of language central to second language learning: the sounds of language, the different grammatical structures, the tools and strategies for learning, the social functions of communication, and the psychology of language learning and use.
Publisher:
ISBN: 9780814254431
Category : Foreign Language Study
Languages : en
Pages : 264
Book Description
Basics of Language for Language Learners, 2nd edition, by Peter W. Culicover and Elizabeth V. Hume, systematically explores all the aspects of language central to second language learning: the sounds of language, the different grammatical structures, the tools and strategies for learning, the social functions of communication, and the psychology of language learning and use.