Machine Learning Fundamentals

Description

This course discusses the fundamentals of machine learning.

Topics include supervised/unsupervised learning, regression, decision trees, ensemble techniques, Vector Support Machines, perception, and multilayer perceptron.

The course focuses on the implementation of these algorithms in Python using Scikit-learn the library.

This course is designed to build the foundation of machine learning and AI and is a prerequisite for most of the advanced courses in AI and Deep Learning.