Our main presenter will be Francis Piéraut on Machine Learning empowered by Python as announced during the flash introduction in Montreal-Python 5.
Machine Learning is a subfield of AI that considers learning patterns from existing data. Related applications are increasing in many fields where adaptive systems are needed, like fraud detection, face recognition, recommendation systems, disambiguation systems, insurance risk estimation, web traffic filtering, voice recognition, and many others.
The first part of this presentation will cover the basics of machine learning; in the second part, we will dive into a real example and see the complete process of using machine learning to create a real-time digit recognition system using Mlboost, a python library. The practical approach should allow the audience to assimilate the most important concepts of machine learning and the critical need for data preprocessing.
After a Software Engineer degree, Francis Piéraut made a research master in Machine Learning at LISA. During his research work, he developed flayers, a powerful C++ neural network library. During the beginning of his career, his spend several years in Montreal startups companies applying Machine Learning and statistical AI related solutions. In 2005, he released the first version of MLboost, a python library that allows him to speedup his Machine Learning projects by simplifying data preprocessing, features selection and data visualization.
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