Step by Step Guide to Machine Learning

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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 to Machine Learning & Data Wrangling
   
   
2. 
   Linear Models, Trees & Preprocessing
   
   
3. 
   Model Evaluation, Feature Selection & Pipelining
   
   
4. 
   Bayes, Nearest Neighbours & Clustering
   
   
5. 
   SVM, Anomalies, Imbalanced Classes, Ensemble Methods
   

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

Instructors: EdYoda Digital University




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