damianstone / ML_lab_sheets

COMS30035 Machine Learning unit

COMS30035 Machine Learning Labs

You are encouraged to install Anaconda (Python 3.7) as it bundles all the course's requirements. Alternatively for manual installation, you will require Python 3.7.x with 'Jupyter' and 'iPython' both possibly in version 4.x.x. All the packages needed will be listed at the beginning of each lab sheet.

If you login remotely to the university Linux machines, you should be able to just run Jupyter Notebook with this command

$ /opt/anaconda3-4.4.0/bin/jupyter notebook

For help on logging in remotely to Bristol machines see here.

Lab	Labsheet	Answers
1	Introduction to numpy and scikit learn	Link
2	Linear models, neural networks and SVM	Link
3	Probabilistic graphical models	Link
4	Mixture models, K-means and Expectation Maximisation	Link
5	PCA and ICA	Link
6	Hidden Markov Models	Link
7	Decision Trees and Ensemble Methods