The Supervised Machine Learning Course

The Supervised Machine Learning Course Description

This course helps you study the theory underlying each of the six algorithms before utilizing Python’s sci-kit and learn package to apply your knowledge to real-world case studies that are specific to each method.

Here’s what you will learn in this book:

• Introduction
• Setting up the Environment
• Naive Bayes
• K-Nearest Neighbors
• Decision Trees and Random Forests
• Support Vector Machines
• Ridge and Lasso Regression