This Machine Learning with Python course dives into the basics of Machine Learning using Python, an approachable and well-known programming language. You'll learn about Supervised vs Unsupervised Learning, look into how Statistical Modeling relates to Machine Learning, and do a comparison of each.
You'll look at real-life examples of Machine Learning and how it affects society in ways you may not have guessed!
We'll explore many popular algorithms including Classification, Regression, Clustering, and Dimensional Reduction and popular models such as Train/Test Split, Root Mean Squared Error and Random Forests.
Most importantly, you will transform your theoretical knowledge into practical skill using hands-on labs. Get ready to do more learning than your machine!
Module 1 - Introduction to Machine Learning
Applications of Machine Learning
Supervised vs Unsupervised Learning
Python libraries suitable for Machine Learning
Module 2 - Regression
Model evaluation methods
Module 3 - Classification
Support Vector Machines
Module 4 - Unsupervised Learning
Module 5 - Recommender Systems
Content-based recommender systems