Assignments completed for a machine learning bootcamp at McGill University.
This assignment consisted in implementing linear regression from scratch both through the ordinary closed-form least-squares solution and through gradient descent. In this assignment, we also explored problems of overfitting and methods such as regularization and hyperparameter search.
In this assignment, sentiment analysis using a Naive Bayes classifier, an SVM and random forests were implemented. Additionally, hyperparameter tuning with GridSearch was explored.
In this assignment, we implemented a facial recognition algorithm using our own custom implementation of PCA.