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Deep Learning Illustrated_A Visual, Interactive Guide to Artificial Intelligence

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"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."

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Uploaded on
August 2, 2024
Number of pages
383
Written in
2022/2023
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Presentation
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,Figures

Tables

Examples

Foreword

Preface

Acknowledgments

About the Authors

I Introducing Deep Learning

1 Biological and Machine Vision

Biological Vision

Machine Vision

The Neocognitron

LeNet-5

The Traditional Machine Learning Approach

ImageNet and the ILSVRC

AlexNet

TensorFlow Playground

Quick, Draw!

Summary

2 Human and Machine Language

Deep Learning for Natural Language Processing

Deep Learning Networks Learn Representations Automatically

Natural Language Processing

,A Brief History of Deep Learning for NLP

Computational Representations of Language

One-Hot Representations of Words

Word Vectors

Word-Vector Arithmetic

word2viz

Localist Versus Distributed Representations

Elements of Natural Human Language

Google Duplex

Summary

3 Machine Art

A Boozy All-Nighter

Arithmetic on Fake Human Faces

Style Transfer: Converting Photos into Monet (and Vice Versa)

Make Your Own Sketches Photorealistic

Creating Photorealistic Images from Text

Image Processing Using Deep Learning

Summary

4 Game-Playing Machines

Deep Learning, AI, and Other Beasts

Artificial Intelligence

Machine Learning

Representation Learning

, Artificial Neural Networks

Deep Learning

Machine Vision

Natural Language Processing

Three Categories of Machine Learning Problems

Supervised Learning

Unsupervised Learning

Reinforcement Learning

Deep Reinforcement Learning

Video Games

Board Games

AlphaGo

AlphaGo Zero

AlphaZero

Manipulation of Objects

Popular Deep Reinforcement Learning Environments

OpenAI Gym

DeepMind Lab

Unity ML-Agents

Three Categories of AI

Artificial Narrow Intelligence

Artificial General Intelligence

Artificial Super Intelligence
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