GitHub - te87037/Octava2

Branches Tags

Name		Name	Last commit message	Last commit date
Latest commit History 4 Commits
Anomaly Detection and Recommender Systems		Anomaly Detection and Recommender Systems
DecisionTrees &Boosting		DecisionTrees &Boosting
HMM		HMM
K-Means Clustering and PCA		K-Means Clustering and PCA
Lectures		Lectures
Linear Regression		Linear Regression
Logistic Regression		Logistic Regression
Multi-class classification and neural networks		Multi-class classification and neural networks
Neural network learning		Neural network learning
Regularized linear regression and bias-variance		Regularized linear regression and bias-variance
Support Vector Machines		Support Vector Machines
README		README

Repository files navigation

These are some programming exercise of Stanford Machine Learning Online Course.
The algorithms were coded in python or matlab including:
1.Anomaly Detection and Recommender Systems
2.Decision Trees&Boosting 
3.HMM
4.K-Means Clustering and PCA
5.Linear Regression
6.Logistic Regression (matlab/octave)
7.Multi-class classification and neural networks
8.Neural network learning
9.Regularized linear regression and bias-variance
10.Support Vector Machiness