leenamurgai / ml-class

Stanford's 2011 Machine Learning Class (Andrew Ng)

ml-class

Stanford's 2011 Machine Learning Class (Andrew Ng)

Course Notes

1. Introduction
2. Linear representation with one variable
3. Linear representation with multiple variables
4. Octave
   • Exercise 1: Linear regression
5. Logistic regression
6. Regularisation
   • Exercise 2: Logistic regression
7. Neural network representation
   • Exercise 3: Multi-class classification & neural networks
8. Neural network learning
   • Exercise 4: Neural networks learning
9. Machine learning application advice
10. Machine learning system design
    • Exercise 5: Regularised linear regression & bias vs variance
11. Support vector machines
    • Exercise 6: SVMs
12. Clustering
13. Dimensionality reduction
    • Exercise 7: K-means clustering & PCA
14. Anomaly detection
15. Recommender systems
    • Exercise 8: Anomaly detection & recommender systems
16. Large scale machine learning
17. Application example: photo OCR