A repository to store the programming files of Machine Learning Lab course.
- Hebb's rule implementation
- Perceptron neuron implementation
- Find S algorithm
- Candidate elimination algorithm
- Data visualization (getting started with matplotlib and seaborn)
- Bivariate Guassian distribution visualization (animation gif)
- K Means clustering (using CTypes module for distance calculations, available distances are:
['Euclidean', 'Manhattan', 'Minkowski', 'Supremum']. - K Near Neighbours (update required)
(May take some time to load due to high quality animations)
-
Shifting mean
-
Changing the Covariance matrix
- Clustering example GIF
