These are the programming assignments from Coursera's Machine Learning course taught by Andrew Ng.

Include:\

Linear Regression (one variable and multiple variables)
Logistic Regression
Regularization
Neural networks
Support Vector Machine
Clustering
Dimensionality Reduction\

EX8

1. Anomaly Detection
2. Movies Recommender System using collaborative filtering learning algorithm

files used

• ex8.m - Octave/MATLAB script for first part of exercise
• ex8 cofi.m - Octave/MATLAB script for second part of exercise
• ex8data1.mat - First example Dataset for anomaly detection
• ex8data2.mat - Second example Dataset for anomaly detection
• ex8 movies.mat - Movie Review Dataset
• ex8 movieParams.mat - Parameters provided for debugging
• multivariateGaussian.m - Computes the probability density function for a Gaussian distribution
• visualizeFit.m - 2D plot of a Gaussian distribution and a dataset
• checkCostFunction.m - Gradient checking for collaborative filtering
• computeNumericalGradient.m - Numerically compute gradients v1fmincg.m - Function minimization routine (similar to fminunc)
• loadMovieList.m - Loads the list of movies into a cell-array
• movie ids.txt - List of movies
• normalizeRatings.m - Mean normalization for collaborative filtering
• submit.m - Submission script that sends your solutions to our servers
• estimateGaussian.m - Estimate the parameters of a Gaussian dis- tribution with a diagonal covariance matrix
• selectThreshold.m - Find a threshold for anomaly detection
• cofiCostFunc.m - Implement the cost function for collaborative fil- tering