MISCADA
Machine Learning
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Lectures
Lecture 1
Machine learning
Perceptron
Perceptron Demo
Lecture 2
Logistic regression
Loss functions
Lecture 3
Loss functions
ROC curve
Support vector machine
Lecture 4
Learning Curves
Non-linear Models
Regularisation
Lecture 5
Neural networks
Variance Bias Trade-off
Lecture 6
Neural network training
Lecture 7
k-Neighbours
Principal component analysis
The curse of dimensionality
Lecture 8
Using Pandas
Using scikit-learn
Slides
Lecture 1
Lecture 2
Lecture 3
Lecture 4
Lecture 5
Lecture 6
Lecture 7
Lecture 8
Literature
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Welcome to the Machine learning course Webpage 25-26
Summative:
Released 13th Jan 2026 at 2 pm and collected 2 pm 14th Jan 2026
Contact
Contact: will.yeadon@durham.ac.uk
Office hours: PH304 Rochester 13:00 - 15:00 Wednesdays
Links
Notebook server
https://miscada-ml-2526.notebooks.danielmaitre.phyip3.dur.ac.uk/
Matplotlib manual
https://matplotlib.org/
scikit-learn manual
http://scikit-learn.org/stable/