- 1 Introduction
- 2 Linear regression with multiple variables.md
- 3 Logistic regression regularization.md
- 4 Neural networks.md
- 5 Neural networks learning.md
- 6 Advice for applying machine learning.md
- 7 Machine learning system design.md
- 8 Support vector machines.md
- 9 Unsupervised learning dimensionality reduction.md
- 10 Dimensionality reduction.md
- 11 Anormaly detection.md
- 12 Recommander systems.md
- 13 Large scale machine learning.md
- 14 Application example photo ocr.md
- 15 Vectorized implementations in octave.md
- ex2.1 Logistic regression
- ex2.2 Regularized logistic regression
- ex3 1 Multi class classification
- ex3 2 Neural networks
- ex4 1 Neural networks
- ex4 2 Backpropagation
- ex5 Regularized Linear Regression and Bias-Variance
- ex6 1 Support vector machines
- ex6 2 Spam classification
- ex7 K-means clustering and pca
- ex8 Recommander system