This repository contains my personal implementations, and notes from the Machine Learning Specialization by Andrew Ng (Stanford University & DeepLearning.AI).
It serves as both a study companion and a practical reference for core machine learning concepts, implemented from scratch and using modern Python tools.
The Machine Learning Specialization is a foundational course that covers the key principles of supervised and unsupervised learning, linear regression, logistic regression, neural networks, and more.
This repo includes:
- Rewritten and optimized versions of the original course labs.
- Notes summarizing mathematical derivations and algorithm intuition.