Solutions to the assignments of the CPSC 540 Machine Learning course (2013) taught by Nando de Freitas. For video lectures and slides click here.

[1.1 Ridge Regression](http://nbviewer.ipython.org/github/diktat/CPSC540machinelearning/blob/master/1.1 Ridge Regression.ipynb)

[1.2 Bayesian Linear Regression](http://nbviewer.ipython.org/github/diktat/CPSC540machinelearning/blob/master/1.2 Bayesian Linear Regression.ipynb)

[1.3 Dual Form of Ridge Regression](http://nbviewer.ipython.org/github/diktat/CPSC540machinelearning/blob/master/1.3 Dual Form of Ridge Regression.ipynb)

[1.4 Collaborative Filtering for Movie Recommendation](http://nbviewer.ipython.org/github/diktat/CPSC540machinelearning/blob/master/1.4 Collaborative Filtering for Movie Recommendation.ipynb)

[2.1 Bias Variance Trade-off](http://nbviewer.ipython.org/github/diktat/CPSC540machinelearning/blob/master/2.1 Bias Variance Trade-off.ipynb)

[2.2 Entropy of a Gaussian Distribution](http://nbviewer.ipython.org/github/diktat/CPSC540machinelearning/blob/master/2.2 Entropy of a Gaussian Distribution.ipynb)

[2.3 Collaborative Filtering for Movie Recommendation](http://nbviewer.ipython.org/github/diktat/CPSC540machinelearning/blob/master/2.3 Collaborative Filtering for Recommendation.ipynb)

[3.1 Gradient and Hessian for logistic regression](http://nbviewer.ipython.org/github/diktat/CPSC540machinelearning/blob/master/3.1 Gradient and Hessian for logistic regression.ipynb)