ml_stanford

This is a set of machine learning algorithms' implementations in Octave as taught by Andrew Ng on Stanford University's Machine Learning course.

The machine learning algorithms hereby implemented are:

Name		Name	Last commit message	Last commit date
Latest commit History 7 Commits
1 - Linear Regression		1 - Linear Regression
2 - Logistic Regression		2 - Logistic Regression
3 - Multiclass Classification		3 - Multiclass Classification
4 - Neural Network Learning		4 - Neural Network Learning
5 - Regularized Linear Regression		5 - Regularized Linear Regression
6 - SVM		6 - SVM
7 - Kmeans and PCA		7 - Kmeans and PCA
8 - Anomaly Detection and Recommender Systems		8 - Anomaly Detection and Recommender Systems
README.md		README.md

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