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Machine learning is central to data science, and there deserves to be a dialogue between the corresponding communities.
In this talk, Sebastien assume you know about overfitting and regularization, and will dissect insidious ways to overfit, as well as the no free lunch theorem. He will explore points of contact between big data and machine learning from an engineering perspective. Finally, Sebastien will present more advanced ML topics which are worth knowing about for data scientists, Bayesian optimization and Auto-ML.
Points of contact between big data engineering and machine learning - Intermediate
Sébastien Bratières has spent 15 years in the speech and language industry in different European ventures, starting from the EU branch of Tellme Networks (now Microsoft) to startups in speech recognition and virtual conversational agents. These days, Sébastien is finishing a PhD in statistical machine learning with Zoubin Ghahramani at the University of Cambridge, UK, and will soon be looking for his next challenges. Sébastien lives in Rome, Italy, with his wife and two children.