This repository contains my handwritten notes on Machine Learning Originally written as a way for me personally to help in understanding the concepts, these notes have lot of diagrams taken from the Andrew Ng course! The target audience was originally me, but anyone is welcome to use it.
-
- Linear regression
- Logistic regression
- Neural networks
- Support vector machines
-
- K-means
- PCA
- Anomaly detection
-
- Recommender systems
- Large scale machine learning
-
- Bias and variance
- Regularization
- What to do next when developing a system
- Algorithm evaluation
- Learning curves
- Error analysis
- Ceiling analysis