This is my code for the practical component of the Undergraduate Machine Learning course at the University of Oxford. Detailed instructions for each exercise can be found in the instructions.pdf file in each subdirectory.
Practical 1 implements Linear Regression with Ridge Regression and Lasso Optimisation. It determines the quality of wine given 11 characteristics. The dataset used can be found here: https://archive.ics.uci.edu/ml/datasets/Wine+Quality. The white wine dataset was used.
Practical 2 is a study comparing a Naive Bayes Classifier with Logistic Regression on the sklearn iris dataset.
Practical 3 implements a convolutional neural network in keras to identify digits on the MNIST dataset. It identifies digits with a 98% accuracy.