This unit seeks to acquaint students with machine learning algorithms which are important in many modern data and computer science applications. We cover topics such as kernel machines, probabilistic inference, neural networks, PCA/ICA, HMMs and emsemble models.
James Cussens (JC) | |
Edwin Simpson (ES) |
Note: For any questions please ask in the appropriate Teams channels or directly to us using Teams chat.
Will Greedy, Amarpal Sahota, Zhijin Guo, James Ward, Henry Bourne, Henry Addison, Carla Rosario
Weeks | Tuesday lecture, 1500-1600, Queens 1.15 | Thursday lab, 0900-1200, MVB 2.11 | Friday lecture, 0900-1000, Queens 1.15 | ||
1 | Introduction [stream]Machine learning concepts [stream] |
L1: Revision of Jupyter Notebook, ML libraries and regression. [answers] | Revisiting regression
[stream], Classification and neural networks [stream] |
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2 | Kernel machines | L2: Classification, nnets and SVMs. [answers] | Introduction to graphical models | ||
3 | Bayesian ML using graphical models | L3: Probabilistic graphical models [answers] | k-means and mixtures of Gaussians | ||
4 | The EM algorithm
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L4: k-means and EM [answers] | PCA | ||
5 | ICA
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L5: PCA and ICA [ answers] | Seqential data | ||
6 | Reading week | ||||
7 | Sequential data | L6: Hidden Markov Models |
Sequential data
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8 | Combining models | L7: Trees and Ensemble methods | Combining models Crowdsourcing and Datasets | ||
9-11 | Coursework weeks | ||||
12 | Review week |
Most (not all) of the software we use in this unit is supplied as Python packages bundled with the Anaconda Python package manager. If you are using the machines in MVB 2.11 to do the lab exercises (as opposed to using your own machine) you need to do the following to start using Anaconda.
module load
anaconda
conda init
conda init
command alters
the .bashrc
file in your home directory to
ensure that you are using the version of Python provided by Anaconda (have
a look at that file if you want). To get the changes
in .bashrc
to take effect the easiest option is
just to kill your terminal window and start up a new one; so
do that.
(base)
that indicates
which Anaconda
environment is currently active.
If you want to do lab exercises on your own machine then you should install Anaconda on it. If you run into installation problems then feel free to ask the Teaching Staff on the unit for help, but we can't guarantee to solve them.
All technical resources will be posted on the COMS30035 Github organisation. If you find any issues, please kindly raise an issue in the respective repository.