Introduction 1 Part 1: Discovering Deep Learning 7 Chapter 1: Introducing Deep Learning 9 Chapter 2: Introducing the Machine Learning Principles 25 Chapter 3: Getting and Using Python 45 Chapter 4: Leveraging a Deep Learning Framework 73 Part 2: Considering Deep Learning Basics 91 Chapter 5: Reviewing Matrix Math and Optimization 93 Chapter 6: Laying Linear Regression Foundations 111 Chapter 7: Introducing Neural Networks 131 Chapter 8: Building a Basic Neural Network 149 Chapter 9: Moving to Deep Learning 163 Chapter 10: Explaining Convolutional Neural Networks 179 Chapter 11: Introducing Recurrent Neural Networks 201 Part 3: Interacting with Deep Learning 215 Chapter 12: Performing Image Classification 217 Chapter 13: Learning Advanced CNNs 233 Chapter 14: Working on Language Processing 251 Chapter 15: Generating Music and Visual Art 269 Chapter 16: Building Generative Adversarial Networks 279 Chapter 17: Playing with Deep Reinforcement Learning 293 Part 4: The Part of Tens 307 Chapter 18: Ten Applications that Require Deep Learning 309 Chapter 19: Ten Must-Have Deep Learning Tools 317 Chapter 20: Ten Types of Occupations that Use Deep Learning 327 Index 335

Learn how deep learning is an essential technologyExperiment with deep learning in a Python environmentSee examples of major deep learning application types Dive deep into deep learning Deep learning provides the means for discerning patterns in the data that drive online business, medicine, research, social media outlets, and many elements of daily life. This book gives you the information you need to take the mystery out of the topic—and all of the underlying technologies associated with it.??In no time, you'll make sense of those increasingly confusing algorithms, and find a simple and safe environment to experiment with deep learning. Inside... Create examples using TensorFlow and KerasBenefit from hands-on activities to make learning easierUse deep learning more effectively with the right toolsMake sense of complex algorithms

Introduction 1 Part 1: Discovering Deep Learning 7 Chapter 1: Introducing Deep Learning 9 Chapter 2: Introducing the Machine Learning Principles 25 Chapter 3: Getting and Using Python 45 Chapter 4: Leveraging a Deep Learning Framework 73 Part 2: Considering Deep Learning Basics 91 Chapter 5: Reviewing Matrix Math and Optimization 93 Chapter 6: Laying Linear Regression Foundations 111 Chapter 7: Introducing Neural Networks 131 Chapter 8: Building a Basic Neural Network 149 Chapter 9: Moving to Deep Learning 163 Chapter 10: Explaining Convolutional Neural Networks 179 Chapter 11: Introducing Recurrent Neural Networks 201 Part 3: Interacting with Deep Learning 215 Chapter 12: Performing Image Classification 217 Chapter 13: Learning Advanced CNNs 233 Chapter 14: Working on Language Processing 251 Chapter 15: Generating Music and Visual Art 269 Chapter 16: Building Generative Adversarial Networks 279 Chapter 17: Playing with Deep Reinforcement Learning 293 Part 4: The Part of Tens 307 Chapter 18: Ten Applications that Require Deep Learning 309 Chapter 19: Ten Must-Have Deep Learning Tools 317 Chapter 20: Ten Types of Occupations that Use Deep Learning 327 Index 335