• Introduction to machine learning concepts and terminology
• The machine learning workflow in Scikit-learn
• Introduction to neural networks and deep learning – the perceptron
• Building and training neural networks with PyTorch and GPUs
• Classification of DNA features using convolutional neural networks
• Regression of DNA binding signal
• Model optimisation – hyperparameter tuning
• Model interpretation – what has my model learned?
• State of the art models – Transformers
• Hackathon day – team competition to build the best performing model
Organisers: Simone Riva, Ed Sanders, David Sims (University of Oxford)
Course Fees: £500 (free for Functional Genomics Initiative participants)
• Includes tea and coffee breaks and a hot lunch in the college dining hall
• Accommodation in college available at an additional cost
Contact [email protected] for more details
Registration:
https://app.onlinesurveys.jisc.ac.uk/s/oxford/ml-in-functional-genomics-course
