Machine Learning For Dummies

Front Cover
John Wiley & Sons, Feb 9, 2021 - Computers - 464 pages
One of Mark Cuban’s top reads for better understanding A.I. (inc.com, 2021)

Your comprehensive entry-level guide to machine learning

While machine learning expertise doesn’t quite mean you can create your own Turing Test-proof android—as in the movie Ex Machina—it is a form of artificial intelligence and one of the most exciting technological means of identifying opportunities and solving problems fast and on a large scale. Anyone who masters the principles of machine learning is mastering a big part of our tech future and opening up incredible new directions in careers that include fraud detection, optimizing search results, serving real-time ads, credit-scoring, building accurate and sophisticated pricing models—and way, way more.

Unlike most machine learning books, the fully updated 2nd Edition of Machine Learning For Dummies doesn't assume you have years of experience using programming languages such as Python (R source is also included in a downloadable form with comments and explanations), but lets you in on the ground floor, covering the entry-level materials that will get you up and running building models you need to perform practical tasks. It takes a look at the underlying—and fascinating—math principles that power machine learning but also shows that you don't need to be a math whiz to build fun new tools and apply them to your work and study.

  • Understand the history of AI and machine learning
  • Work with Python 3.8 and TensorFlow 2.x (and R as a download)
  • Build and test your own models
  • Use the latest datasets, rather than the worn out data found in other books
  • Apply machine learning to real problems

Whether you want to learn for college or to enhance your business or career performance, this friendly beginner's guide is your best introduction to machine learning, allowing you to become quickly confident using this amazing and fast-developing technology that's impacting lives for the better all over the world.

 

Contents

Introduction 1
3
INTRODUCING HOW MACHINES LEARN
7
Learning in the Age of Big Data
23
Having a Glance at the Future
37
PREPARING YOUR LEARNING TOOLS
47
Beyond Basic Coding in Python
67
Working with Google Colab
87
Table of Contents V
92
Leveraging Similarity
221
Working with Linear Models the Easy Way
243
Hitting Complexity with Neural Networks
271
Going a Step Beyond Using Support Vector Machines
307
Classifying and Estimating with SVM
316
Applying Learning to Real Problems
339
Scoring Opinions and Sentiments
361
Recommending Products and Movies
383

Getting a Google Account
94
Getting Started with the Math Basics
115
Descending the Gradient
139
Validating Machine Learning
153
Starting with Simple Learners
175
Taking a Probabilistic Turn
188
Learning from Smart and Big Data
197
The Part of Tens
405
Ten Machine Learning Packages to Master
423
INDEX
431
Machine Learning For Dummies
432
Table of Contents vii
443
Copyright

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About the author (2021)

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.

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