Machine learning
Based on Andrew Ng's CS229 Machine Learning at Stanford University. Refer to his course website for lecture notes, linear algebra review, Matlab tutorial and practice problem sets.
Topic sequence
- Linear Regression
- Logistic Regression
- Multiclass Classification and Neural Networks
- Neural Network
- Linear Regression Bias vs Variance
- Support Vector Machines
- K-means Clustering
- Anomaly Detection
Additional References
- Machine Learning for Hackers by Drew Conway and John White
- Pattern Recognition and Machine Learning by Christopher Bishop
- The Elements of Statistical Learning by Trevor Hastie, Robert Tibshirani and Jerome Friedman
- CMSC 726: Machine Learning at University of Maryland by Héctor Corrada Bravo