MISCADA
Machine Learning
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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Slides
> Lecture 5
Lecture slides as presentation
Lecture 5
Lecture slides as presentation
Neural networks
Variance-Bias tradeoff