Learning to use data by adapting processing method to each problem
Introduction
Machine learning overview: Concepts and glossary – Classification of problems – Algorithm family – Type of learning – Use case
Knowing the steps of a machine learning case
Data preparation: filtering, study of correlations, relevant data organisation – Selection of algorithm solution: regression, clustering, classification – Evaluation criteria
Understanding machine learning
Method mapping – Model choice – Existing tools – Possible results – Example on a relevant case
Discovering easy-to-use tools for machine learning
Presentation of tools to implement intelligent solutions
Presentation of Deep Learning tools
Image classification