Machine Learning and Data Mining (2 º Sem 2020/2021)

1.Supervised learning: regression and classification
2.Regularized linear models: ridge, lasso and elastic net.
3.k-nearest neighbors
4.Decision trees
5.Naïve Bayes methods
6.Support vector machines
7.Neural networks and deep learning
8.Ensemble methods: bagging, boosting and random forests
9.Unsupervised learning