Machine learning is fascinating, but those math-heavy tutorials can be intimidating, even for a programmer. In this course, How Machine Learning Works, you’ll learn the basics of machine learning from code. First, you will have a look at supervised learning, and you’ll quickly move to coding your first learning program, and see how to improve that program line by line. Then, you’ll discover how to improve that program line by line. Finally, you’ll see how to write this program by yourself, without resorting to obscure machine learning libraries. By the end of the course, you’ll have a working computer vision program that recognizes handwritten characters, and you’ll have practical knowledge of the foundational ideas of machine learning.
Author Name: Paolo Perrotta
Author Description:
Paolo Perrotta is the author of “Programming Machine Learning” and “Metaprogramming Ruby”. He has hundreds of articles, conference speeches and training deliveries under his belt. He developed software in domains ranging from automotive to healthcare, large-scale web sites, and computer games.

Table of Contents

• Course Overview
  2mins
• Introduction
  11mins
• Building Your First Machine Learning Program
  25mins
• Improving the Algorithm with Gradient Descent
  17mins
• Expanding Regression to Multiple Variables
  24mins
• Predicting Discrete Outcomes
  15mins
• Recognizing Individual Digits
  18mins
• Figuring Out Image Recognition
  15mins
• Seeing the Big Picture
  12mins