If you are looking to start your career in machine learning then this is the course for you.

This is a course designed in such a way that you will learn all the concepts of machine learning right from basic to advanced levels.

This course has 5 parts as given below:

1. Introduction & Data Wrangling in machine learning

2. Linear Models, Trees & Preprocessing in machine learning

3. Model Evaluation, Feature Selection & Pipelining in machine learning

4. Bayes, Nearest Neighbours & Clustering in machine learning

5. SVM, Anomalies, Imbalanced Classes, Ensemble Methods in machine learning

For the code explained in each lecture, you can find a GitHub link in the resources section.