ML-From-Scratch

*Learn Machine Learning with these amazing GitHub repositories! * 1⃣ [ML for Beginners](https://github.com/microsoft/ML-For-Beginners) by Microsoft 2⃣ [100 Days of ML Code](https://github.com/Avik-Jain/100-Days-Of-ML-Code) by Avik Jain 3⃣ [ML From Scratch](https://github.com/eriklindernoren/ML-From-Scratch) by Erik Linder-Noren 4⃣ [Hands-On ML](https://github.com/ageron/handson-ml2) by Ageron 5⃣ [Awesome Machine Learning](https://github.com/josephmisiti/awesome-machine-learning) by Joseph Misiti Save & Share for quick access! #MachineLearning #GitHub #AI #LearnML

Interesting find. Just FYI, this repo has been the OG for several years, when it comes to building NN from scratch: https://github.com/eriklindernoren/ML-From-Scratch

Here is something you should check out in that case https://github.com/eriklindernoren/ML-From-Scratch . Although be warned, everything from scratch approach l, despite being addictive, is harder than standing on shoulders of giants and takes too much resilience. If you are even a bit of procrastinater like me, it's tend to stay a sweet fantasy a lot of times. It's only when I was half working on a project and had no other option, I could go for implementing my first algorithm from scratch.

scikit-learn is a production ready library that has some very well commented and easy to read source code. https://github.com/eriklindernoren/ML-From-Scratch is an easy to understand understand implementation of some the basic ML algorithms built from first principles and aims for readability over performance.