Machine Learning Notes

A collection of structured notes covering the fundamental concepts of Machine Learning.

These notes are written while studying and organized by topic to make revision and review easier.

Topics

#	Topic
1	Linear Regression
2	Gradient Descent
3	Logistic Regression
4	Neural Networks
5	Practical Machine Learning
6	Decision Trees
7	Tree Ensembles
8	Clustering
9	Anomaly Detection
10	Recommender Systems
11	Principal Component Analysis (PCA)
12	Reinforcement Learning

Course

These notes are based on Andrew Ng's Machine Learning Specialization by DeepLearning.AI and Stanford Online.

Course: Machine Learning Specialization

Purpose

The goal of this repository is to document my learning journey through Machine Learning concepts and provide a structured reference for revision and future projects.

---