100-Days-Of-MachineLearning-Code

Machine Learning is the “Field of study that gives computers the ability to learn without being explicitly programmed”. — Arthur Samuel , 1959

I am passionate in Machine Learning (it goes without saying as I am doing my PhD in Machine Learning). One day I came across this video by Siraj Raval, in which he talked about #100daysofMLcode Challenge. I know I am bit (maybe too late) for this challenge, but better late than never. #100daysofMLcode challenge means, studying and/or coding machine learning for minimum 1 hour a day for next 100 days.

This repository contains 100-Days-Of-Machine-Learning-Code. In addition to that, it’s a my place to store all my machine learning self learning resources and place to track my progress.

By doing this challenge, I would like to learn Machine Learning (from scratch), which is important and helpful. Note that I am aware with many thing as I am doing my research in Machine Learning, however I want to start from the scratch. Starting from scratch will help me to build strong foundation of machine learning. In addition to that, at the end of 100 days, I hope to have a rich portfolio of code, projects, and summary of the machine learning topics and models plus all of the additional content (available on internet) which I’ll discover over the learning journey. I think, most importantly – as a researcher, I’d like to contribute to the machine learning community.

My aim throughout this process will be to learn as much as I can with accessible materials (mostly free) while always being sure to provide useful links that help someone wants to learn machine learning.

You can find my Progress of Round 1 here.

You can find my Progress of Round 2 here.