Machine Learning For Dummies

ISBN-13: 9781119724018 / Angielski / Miękka / 2021 / 464 str.

John Paul Mueller; Luca Massaron

Spis treści

Introduction 1Part 1: Introducing How Machines Learn 5Chapter 1: Getting the Real Story about AI 7Chapter 2: Learning in the Age of Big Data 23Chapter 3: Having a Glance at the Future 37Part 2: Preparing Your Learning Tools 47Chapter 4: Installing a Python Distribution 49Chapter 5: Beyond Basic Coding in Python 67Chapter 6: Working with Google Colab 87Part 3: Getting Started with the Math Basics 115Chapter 7: Demystifying the Math Behind Machine Learning 117Chapter 8: Descending the Gradient 139Chapter 9: Validating Machine Learning 153Chapter 10: Starting with Simple Learners 175Part 4: Learning from Smart and Big Data 197Chapter 11: Preprocessing Data 199Chapter 12: Leveraging Similarity 221Chapter 13: Working with Linear Models the Easy Way 243Chapter 14: Hitting Complexity with Neural Networks 271Chapter 15: Going a Step Beyond Using Support Vector Machines 307Chapter 16: Resorting to Ensembles of Learners 319Part 5: Applying Learning to Real Problems 339Chapter 17: Classifying Images 341Chapter 18: Scoring Opinions and Sentiments 361Chapter 19: Recommending Products and Movies 383Part 6: The Part of Tens 405Chapter 20: Ten Ways to Improve Your Machine Learning Models 407Chapter 21: Ten Guidelines for Ethical Data Usage 415Chapter 22: Ten Machine Learning Packages to Master 423Index 431

O autorze

John Mueller has produced hundreds of books and articles on topics ranging from networking to home security and from database management to heads-down programming.Luca Massaron is a senior expert in data science who has been involved with quantitative methods since 2000. He is a Google Developer Expert (GDE) in machine learning.