Deep Learning Illustrated
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Deep Learning Illustrated
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Author : Jon Krohn
language : en
Publisher: Addison-Wesley Professional
Release Date : 2019-08-05
Deep Learning Illustrated written by Jon Krohn and has been published by Addison-Wesley Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-08-05 with Computers categories.
"The authors’ clear visual style provides a comprehensive look at what’s currently possible with artificial neural networks as well as a glimpse of the magic that’s to come." – Tim Urban, author of Wait But Why Fully Practical, Insightful Guide to Modern Deep Learning Deep learning is transforming software, facilitating powerful new artificial intelligence capabilities, and driving unprecedented algorithm performance. Deep Learning Illustrated is uniquely intuitive and offers a complete introduction to the discipline’s techniques. Packed with full-color figures and easy-to-follow code, it sweeps away the complexity of building deep learning models, making the subject approachable and fun to learn. World-class instructor and practitioner Jon Krohn–with visionary content from Grant Beyleveld and beautiful illustrations by Aglaé Bassens–presents straightforward analogies to explain what deep learning is, why it has become so popular, and how it relates to other machine learning approaches. Krohn has created a practical reference and tutorial for developers, data scientists, researchers, analysts, and students who want to start applying it. He illuminates theory with hands-on Python code in accompanying Jupyter notebooks. To help you progress quickly, he focuses on the versatile deep learning library Keras to nimbly construct efficient TensorFlow models; PyTorch, the leading alternative library, is also covered. You’ll gain a pragmatic understanding of all major deep learning approaches and their uses in applications ranging from machine vision and natural language processing to image generation and game-playing algorithms. Discover what makes deep learning systems unique, and the implications for practitioners Explore new tools that make deep learning models easier to build, use, and improve Master essential theory: artificial neurons, training, optimization, convolutional nets, recurrent nets, generative adversarial networks (GANs), deep reinforcement learning, and more Walk through building interactive deep learning applications, and move forward with your own artificial intelligence projects Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.
Deep Learning
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Author : Andrew Glassner
language : en
Publisher: No Starch Press
Release Date : 2021-06-22
Deep Learning written by Andrew Glassner and has been published by No Starch Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-22 with Computers categories.
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
Deep Learning With Python Illustrated Guide For Beginners Intermediates
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Author : William Sullivan
language : en
Publisher: PublishDrive
Release Date : 2018-10-24
Deep Learning With Python Illustrated Guide For Beginners Intermediates written by William Sullivan and has been published by PublishDrive this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-24 with Computers categories.
Deep Learning With Python Illustrated Guide For Beginners And Intermediates "Learn By Doing Approach" Includes Keras with Tensorflow Backend Deep learning originates from a broader family of machine learning, including supervised and unsupervised learning The python programming language is one of the most popular languages for programmers in the 21st century. This programming language has been a fundamental cornerstone in a lot of technology we use today. -Things we take for granted on a daily basis. Developing both desktop and web applications, and more interestingly enough has been used to accomplish many artificial intelligence feats. The world is constantly changing and evolving and it appears machine learning could be the way of the future! As we speak technology on a massive scale is being developed to replace mundane and repetitive tasks humans interface with everyday through the use of "deep learning". Ultimately, this means less human errors and a more efficient ways of operating for many corporations. You can potentially become the next big start-up! Develop software, web development tools and many more online ventures! Companies That Use Python Currently Google Facebook Dropbox Yahoo IBM Mozilla Quora Why Programmers Choose To Use Python? Readable & Maintainable Code Dynamic Type System Compatible with Major Platforms and Systems Robust Standard Library Simplifies Complex Software Development Test Driven Development Highly Sought After Skill-Set For Employers Invest in your knowledge base by buying your copy right now. The greatest investment you can make is an investment in yourself! Python will pave the road of technological advancements and very much so shape the world we live in. Become apart of this global progression towards advanced technology through the use of "deep learning". What You'll Learn What is deep learning Theory of Artificial Neural Network Artificial Neural Network with Keras Image Classification with Convolutional Neural Network Environment Setup Natural Language Processing Evaluating and Tuning the ANN Sequence Modeling And, much, much more! By the end of this book you will have grasped the fundamentals of python programming & deep learning! There is also illustrations to go along to help you understand and retain the info on a much more profound level. Picture diagrams have scientifically proven to accelerate the learning process by over 120%! Buy Your Copy Right Now!
Deep Learning With Tensorflow Keras And Pytorch
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Author : Jon Krohn
language : en
Publisher:
Release Date : 2020
Deep Learning With Tensorflow Keras And Pytorch written by Jon Krohn and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with categories.
7+ Hours of Video Instruction An intuitive, application-focused introduction to deep learning and TensorFlow, Keras, and PyTorch Overview Deep Learning with TensorFlow, Keras, and PyTorch LiveLessons is an introduction to deep learning that brings the revolutionary machine-learning approach to life with interactive demos from the most popular deep learning library, TensorFlow, and its high-level API, Keras, as well as the hot new library PyTorch. Essential theory is whiteboarded to provide an intuitive understanding of deep learning's underlying foundations; i.e., artificial neural networks. Paired with tips for overcoming common pitfalls and hands-on code run-throughs provided in Python-based Jupyter notebooks, this foundational knowledge empowers individuals with no previous understanding of neural networks to build powerful state-of-the-art deep learning models. About the Instructor Jon Krohn is the Chief Data Scientist at the machine learning company untapt. He presents a popular series of tutorials published by Addison-Wesley and is the author of the acclaimed book Deep Learning Illustrated . Jon teaches his deep learning curriculum in-classroom at the New York City Data Science Academy. He holds a doctorate in neuroscience from Oxford University, lectures at Columbia University, and carries out machine vision research at Columbia's Irving Medical Center. Skill Level Intermediate Learn How To Build deep learning models in all the major libraries: TensorFlow, Keras, and PyTorch Understand the language and theory of artificial neural networks Excel across a broad range of computational problems including machine vision, natural language processing, and reinforcement learning Create algorithms with state-of-the-art performance by fine-tuning model architectures Self-direct and complete your own Deep Learning projects Who Should Take This Course Software engineers, data scientists, analysts, and statisticians with an interest in deep learning. Code examples are provided in Python, so familiarity with it or another object-oriented programming language would be helpful. Previous experience with statistics or machine learning is not necessary. Course Requirements Some experience with any of the following are an asset, but none are essential: Object-oriented programming, specifically Python Simple shell commands; e.g., in Bash Machine learning or statistics Lesson Descriptions Lesson 1: Introduction to Deep Learning and Artifi...
King Charles The First S Declaration To His Subjects Concerning Lawful Sports To Be Used On Sundays
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Author : Great Britain. Sovereign (1625-1649 : Charles I)
language : en
Publisher:
Release Date : 1860
King Charles The First S Declaration To His Subjects Concerning Lawful Sports To Be Used On Sundays written by Great Britain. Sovereign (1625-1649 : Charles I) and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1860 with Amusements categories.
Deep Learning With Python Illustrated Guide For Beginners And Intermediates
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Author : William Sullivan
language : en
Publisher:
Release Date : 2018-11-06
Deep Learning With Python Illustrated Guide For Beginners And Intermediates written by William Sullivan and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-06 with Artificial intelligence categories.
Providing a foundation in deep learning, this book is aimed at beginners and intermediate deep learning experts, and covers important concepts and problems in the field. Each chapter begins with theory and follows with a practical implementation in Python. It covers a variety of problems, such as digital recognition, image reclassification, stock market prediction, and NLP problems such as text classification and sentimental analysis. Datasets are provided for each problem so that readers can solve using different algorithms, such as with convolutional neural networks, or with recurrent neural networks.
Machine Vision Gans And Deep Reinforcement Learning
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Author : Jon Krohn
language : en
Publisher:
Release Date : 2020
Machine Vision Gans And Deep Reinforcement Learning written by Jon Krohn and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with categories.
Sneak Peek The Sneak Peek program provides early access to Pearson video products and is exclusively available to Safari subscribers. Content for titles in this program is made available throughout the development cycle, so products may not be complete, edited, or finalized, including video post-production editing. 6 Hours of Video Instruction An intuitive introduction to the latest superhuman capabilities facilitated by Deep Learning. Overview Machine Vision, GANs, Deep Reinforcement Learning LiveLessons is an introduction to three of the most exciting topics in Deep Learning today. Modern machine vision involves automated systems outperforming humans on image recognition, object detection, and image segmentation tasks. Generative Adversarial Networks cast two Deep Learning networks against each other in a "forger-detective" relationship, enabling the fabrication of stunning, photorealistic images with flexible, user-specifiable elements. Deep Reinforcement Learning has produced equally surprising advances, including the bulk of the most widely-publicized "artificial intelligence" breakthroughs. Deep RL involves training an "agent" to become adept in given "environments," enabling algorithms to meet or surpass human-level performance on a diverse range of complex challenges, including Atari video games, the board game Go, and subtle hand-manipulation tasks. Throughout these lessons, essential theory is brought to life with intuitive explanations and interactive, hands-on Jupyter notebook demos. Examples feature Python and straightforward Keras layers in TensorFlow 2, the most popular Deep Learning library. About the Instructor Jon Krohn is Chief Data Scientist at the machine learning company untapt. He presents a popular series of deep learning tutorials published by Addison-Wesley and is the author of the bestselling book Deep Learning Illustrated . Jon teaches his deep learning curriculum in-classroom at the New York City Data Science Academy, as well as guest lecturing at Columbia University and New York University. He holds a doctorate in neuroscience from Oxford University and has been publishing on machine learning in leading journals since 2010. Skill Level Intermediate Learn How To Understand the high-level theory and key language around machine vision, deep reinforcement learning, and generative adversarial networks Create state-of-the art models for image recognition, object detection, and image segmentation Architect GANs that crea...
Omaha Illustrated
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Author : Alfred Rasmus Sorenson
language : en
Publisher:
Release Date : 1888
Omaha Illustrated written by Alfred Rasmus Sorenson and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1888 with Latter Day Saints categories.
Python Machine Learning
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Author : Moubachir Madani Fadoul
language : en
Publisher:
Release Date : 2020-05-31
Python Machine Learning written by Moubachir Madani Fadoul and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-31 with categories.
Have you always wanted to learn deep learning but are afraid it'll be too difficult for you? This book is for you.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.Book DescriptionPython Machine Learning, is a comprehensive guide to machine learning and deep learning with Python. It acts as both a step-by-step tutorial, and a reference you'll keep coming back to as you build your machine learning systems.Packed with clear explanations, visualizations, and working examples, the book covers most of the essential machine learning techniques in depth. While some books teach you only to follow instructions, with this machine learning book, this tutorial book teaches the principles behind machine learning, allowing you to build models and applications for yourself. Updated for TensorFlow, skit-learn, Keras, and theano, this edition introduces readers to its new Keras API features, as well as the latest additions to scikit-learn. It's also expanded to cover cutting-edge reinforcement learning techniques based on deep learning, as well as an introduction to GANs. Finally, this book also explores analysis by giving some examples, helping you learn how to use machine learning algorithms to classify or predict documents output.This book is your companion to machine learning with Python, whether you're a Python developer new to machine learning or want to deepen your knowledge of the latest developments.What you will learn-Master the frameworks, models, and techniques that enable machines to 'learn' from data-Use scikit-learn for machine learning and TensorFlow for deep learning-Apply machine learning to classification, predict predict customer churning, and more-Build and train neural networks, GANs, CNN, and other models-Discover best practices for evaluating and tuning models-Predict target outcomes using optimization algorithm such as Gradient Descent algorithm analysis-Overcome challenges in deep learning algorithms by using dropout, regulation-Who This Book Is ForIf you know some Python and you want to use machine learning and deep learning, pick up this book. Whether you want to start from scratch or extend your machine learning knowledge, this is an essential resource. Written for developers and data scientists who want to create practical machine learning and deep learning code, this book is ideal for anyone who wants to teach computers how to learn from data.Table of Contents1.Giving Computers the Ability to Learn from Data2.Training Simple ML Algorithms for Classification3.ML Classifiers Using scikit-learn4.Building Good Training Datasets - Data Preprocessing5.Compressing Data via Dimensionality Reduction6.Best Practices for Model Evaluation and Hyperparameter Tuning7.Combining Different Models for Ensemble Learning8.Predicting Continuous Target Variables with supversized learning 9.Implementing Multilayer Artificial Neural Networks10.Modeling Sequential Data Using Recurrent Neural Networks11.GANs for Synthesizing New Data...and so much more....In every chapter, you can edit the examples online
The Illustrated History And Biography Of Brecknockshire From The Earliest Times To The Present Day
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Author : Edwin Poole
language : en
Publisher:
Release Date : 1886
The Illustrated History And Biography Of Brecknockshire From The Earliest Times To The Present Day written by Edwin Poole and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1886 with Breconshire (Wales) categories.