
Video description
In Video Editions the narrator reads the book while the content, figures, code listings, diagrams, and text appear on the screen. Like an audiobook that you can also watch as a video.
Did you think machine learning is complicated and hard to master? It’s not! Read this book! Serrano demystifies some of the best-held secrets of the machine learning society.
Sebastian Thrun, Founder, Udacity
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
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 audience
No machine learning knowledge necessary, but basic Python required.about the author
Luis G. Serrano is a research scientist in quantum artificial intelligence. Previously, he was a Machine Learning Engineer at Google and Lead Artificial Intelligence Educator at Apple.The first step to take on your machine learning journey.
Millad Dagdoni, Norwegian Labour and Welfare Administration
A nicely written guided introduction, especially for those who want to code but feel shaky in their mathematics.
Erik D. Sapper, California Polytechnic State University
The most approachable introduction to machine learning I’ve had the pleasure to read in recent years. Highly recommended.
Kay Engelhardt, devstats
NARRATED BY MARIANNE SHEEHAN