Discover valuable machine learning techniques you can understand and apply using just high school math.

In Grokking Machine Learning, you will learn:

• Supervised algorithms for classifying and splitting data
• Methods for cleaning and simplifying data
• Machine learning packages and tools
• Neural networks and ensemble methods for complex datasets

Grokking Machine Learning teaches you how to apply ML to your projects using only standard Python code and high school-level math. No specialist knowledge is required to tackle the hands-on exercises using Python and readily available machine learning tools. Packed with easy-to-follow Python-based exercises and mini-projects, this book sets you on the path to becoming a machine learning expert.

About the technology

Discover powerful machine learning techniques you can understand and apply using only high school math! Put simply, machine learning is a set of techniques for data analysis based on algorithms that deliver better results as you give them more data. ML powers many cutting-edge technologies, such as recommendation systems, facial recognition software, smart speakers, and even self-driving cars. This unique book introduces the core concepts of machine learning, using relatable examples, engaging exercises, and crisp illustrations.

About the book

Grokking Machine Learning presents machine learning algorithms and techniques in a way that anyone can understand. This book skips the confused academic jargon and offers clear explanations that require only basic algebra. As you go, you’ll build interesting projects with Python, including models for spam detection and image recognition. You’ll also pick up practical skills for cleaning and preparing data.

About the listener

For listeners who know basic Python. No machine learning knowledge necessary.

About the author

Luis G. Serrano is a research scientist in quantum artificial intelligence. Previously, he was an ML Engineer at Google and Lead AI Educator at Apple.

PLEASE NOTE: When you purchase this title, the accompanying PDF will be available in your Audible Library along with the audio.