Description


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:


Introduction & Data Wrangling in machine learning


Linear Models, Trees & Preprocessing in machine learning


Model Evaluation, Feature Selection & Pipelining in machine learning


Bayes, Nearest Neighbors & Clustering in machine learning


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.


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