This repository contains the documented example codes of Scikit-Learn, This repository will be useful for Machine Learning staters who find difficult to understand the example codes.
This repo also provides the workflow to the self-starters how to getting started with ML and provides which topic you should complete first.
I'm using codes that are available on Scikit-Learn
Link -> http://scikit-learn.org/stable/index.html
How to start in this repo?
Follow these folders
Pre-Processsing :- Preproceeing step is important because in real world you will always collect dirty data. You have to make it ready so that it can be used for further process.
Feature Selection :- Next step is Feature Selection, In this step we select those attributes(Features) that are most relevant to your predictive modeling problem.
Feature Selection is not Dimension Reduction.
Linear Algerbra (One of the most important topic you should know)
Gilbert Strang: -> https://ocw.mit.edu/courses/mathematics/18-06-linear-algebra-spring-2010/index.htm
You can also search for videos on youtube provided by MIT OpenCourseWare
Statistics and probability
NPTEL MOOC -> NOC15 July-Sep MG05