Machine Learning

Pre-process the data to suit the models used

Evaluate a model using cross-validation and different metrics

Mastering the overall algorithms of boosting and bagging type

Select and optimize a Machine Learning algorithm

Identify unsupervised Machine Learning problems

Mastering the main clustering algorithms using a key library in Machine Learning, scikit-learn

Mastering logistic regression, penalized and Elastic-Net models

Know the main evaluation metrics of the regression models used in Machine Learning.

Optimally reduce the size of a dataset without loss of information

Visually locate structures in order to determine the appropriate Machine Learning algorithm