Introduction 1 Part 1: Introducing How Machines Learn 5 Chapter 1: Getting the Real Story About AI 7 Chapter 2: Learning in the Age of Computers 23 Chapter 3: Having a Glance at the Future 35 Part 2: Learning Machine Learning by Coding 45 Chapter 4: Working with Google Colab 47 Chapter 5: Understanding the Tools of the Trade 71 Chapter 6: Getting Beyond Basic Coding in Python 81 Part 3: Building the Foundations 103 Chapter 7: Demystifying the Math Behind Machine Learning 105 Chapter 8: Descending the Gradient 129 Chapter 9: Validating Machine Learning 145 Part 4: Learning from Smart Algorithms 169 Chapter 10: Starting with Simple Learners 171 Chapter 11: Leveraging Similarity 195 Chapter 12: Working with Linear Models the Easy Way 219 Chapter 13: Going Beyond the Basics with Support Vector Machines 251 Chapter 14: Tackling Complexity with Neural Networks 263 Chapter 15: Resorting to Ensembles of Learners 303 Part 5: Applying Learning to Real Problems 327 Chapter 16: Classifying Images 329 Chapter 17: Scoring Opinions and Sentiments 351 Chapter 18: Recommending Products and Movies 379 Part 6: The Part of Tens 401 Chapter 19: Ten Ways to Improve Your Machine Learning Models 403 Chapter 20: Ten Guidelines for Ethical Data Usage 411 Index 419.