Mastery of Python
Good knowledge of Dataviz
Skills acquired at the end of the course:
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
Supervised Machine Learning
Non-supervised Machine Learning
Les prochaines dates :
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