This repo is comprised of studies developed while reading the Hands-on Machine Learning book, by Aurélien Géron.
- Classification: contains implementation of traditional metrics used on classification tasks using Python and Scikit-Learn based on some examples.
- Training models: examples of gradient descent, polynomial regression, learning curves and logistic regression
- Support Vector Machines: contains implementation of Support Vector Machine for classification and regression tasks
- Decision trees: contains implementation of Decision Trees for classification and regression
- Ensemble Learning: brings concepts like voting classifier, bagging, pasting, boosting and stacking
- Dimensionality Reduction: contains implementation of PCA
- Clustering: contains implementation of important techniques such as KMeans and DBSCAN