Description

In this course,

First, you will learn how rule-based and ML-based systems differ and their strengths and weaknesses and how supervised and unsupervised learning models differ from each other.

Next, you will discover how to implement a range of techniques to solve the supervised learning problems of classification and regression. You will gain an intuitive understanding of the the model algorithms you can use for classification and regression.

Finally, you will round out your knowledge by building clustering models using a couple of different algorithms, and validating the results. When you’re finished with this course, you will have the skills and knowledge to identify the correct machine learning problem setup, and the appropriate solution and evaluation techniques for your use-case.