Resources

Below is a list of Machine Learning tutorials and resources that we have found useful. If you find something that you think should be added to the list, please let us know!

Courses

Coursera

Coursera is an open online course provider, and with your University of Leeds login, you can have free access to thousands of courses, from hundreds of universities.

Name Host Description
Mathematics for Machine Learning Specialization Coursera Prerequisite mathematics for applications in data science and machine learning.
Machine Learning Theory and Hands-on Practice with Python Specialization Coursera Develop Foundational Machine Learning Skills. Add Supervised, Unsupervised, and Deep Learning techniques to your Data Science toolkit.
Deep learning in Electronic Health Records Coursera Train deep learning architectures such as Multi-layer perceptron, Convolutional Neural Networks and Recurrent Neural Networks for classification.
Deep Learning with PyTorch, Image Segmentation Coursera Using U-Net architecture for segmentation.
TensorFlow 2 for Deep Learning Specialization Coursera TensorFlow 2.
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University of Leeds

To get on any University of Leeds module (to attend lectures and have access to course materials) email the module leader, explaining that you are a PhD student wanting to take their module.

You do not have to be in the School of Computer Science to take the computing modules, but:

  • Check you satisfy the prerequisites of the modules (ask your supervisor if you are unsure).
  • You should ask your supervisor if the module is relevant to your project.
  • You may find getting on the module more challenging if you are coming from another school (especially those not in Engineering and Physical Sciences faculty (EPS)).
  • You can ask us at SciML (or your supervisor) to advocate for you to get on these modules.

SciML are working on getting access to the course materials, but if you are not on minerva you will not be able to attend the lectures themselves.

Name Host Description
COMP3611 Machine Learning University of Leeds 3rd year undergraduate module that runs in semester 1. Module leader is Dr Marc de Kamps (M.deKamps@leeds.ac.uk).
COMP5611M Machine Learning University of Leeds Taught masters module that runs in semester 2. The module leader is Dr Yanlong Huang ( Y.L.Huang@leeds.ac.uk).
COMP5625M Deep Learning University of Leeds Taught masters module that runs in semester 2. The module leader is Dr Sharib Ali (S.S.Ali@leeds.ac.uk).
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Notebooks

Name Organisation Description
CEMAC Jupyter Notebooks LIFD and CEMAC, University of Leeds Jupyter notebook tutorials on Convolutional Neural Networks (CNNs), Physics Informed Neural Networks (PINNs), Gaussian Processes, Random Forests, Generative Adversarial Networks (GANs), Auto Encoders, Dimensionality Reduction and XGBoost.
The Turing Way The Alan Turing Institute Handbook to reproducible, ethical and collaborative data science. Includes information on version control, open-source code and licensing.
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Books and Articles

Name Author Description
Deep Learning Ian Goodfellow, Yoshua Bengio, Aaron Courville Comprehensive guide to all of the basic machine learning tools.
Programming pytorch for deep learning Ian Pointer Build basic models alongside this book, which comes with coding projects and model solutions.
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