Machine Learning: The Mastery Bible

Machine learning can seem like a collection of algorithms and technical terms; this guide takes a wider view. Bill Hanson introduces the field, traces some of its history, and connects its core ideas to data analysis, Python, artificial intelligence, and business applications. The result is a broad orientation for readers who want to understand what machine learning is and where it is used.

From the origins of the field to modern applications

The book begins with the history of machine learning before turning to its different types and commonly used algorithms or models. This opening context helps place today’s interest in learning systems within a longer story of efforts to make sense of data and automate aspects of analysis.

Understand the ideas behind the models

Chapters explore artificial intelligence, data in machine learning, data analysis, and comparisons between models. The coverage also reaches neural networks and deep learning, giving readers a broad map of related concepts rather than focusing on just one technique.

Python, model building, and practical use

Python and the process of building machine-learning models are among the subjects addressed. The guide also considers applications across business, with dedicated attention to what business leaders should know and how machine learning is used in marketing.

Who may find this guide useful?

This book may suit readers looking for an introductory overview of machine learning and its connections to data science and business. Its wide-ranging chapter plan can help newcomers orient themselves among the field’s main themes, while business readers may appreciate the attention given to marketing and organizational applications.

For a first pass through the landscape—from algorithms and analysis to applications—Machine Learning: The Mastery Bible brings the major topics together in one survey.