Machine Learning Algorithms: Supervised Learning Tip to Tail

This course will teach you the basics of machine-learning projects. This course will teach you how to use supervised learning techniques in real-world cases. This course will enable you to identify the business situations where decision trees, support vector machines, and knearest neighbours are most effective. Learners will be able to discuss common problems in applied ML and compare the effects of different data preparation methods.

To be successful with Python programming, you should have a basic understanding. This includes the ability to code trace existing codes and read and write conditionals and loops. Basic knowledge of linear algebra (vectornotation) and statistics (probability, median/mode) are required. This course is part of the Applied Machine Learning Specialization. It's brought to you by Coursera & Alberta Machine Intelligence Institute.