Following Nick's wonderful introduction to machine learning, we have another fascinating talk, this time by Praneeth V of Blinq Media, diving deeper into some theory behind supervised machine learning (e.g. classification).
Speaker: Praneeth Vepakomma, Senior Data Scientist, Blinq Media
Summary: Supervised machine learning algorithms primarily focus on prediction and classification problems with limited data. The concepts of generalization and predictability are the building blocks behind the working of a supervised learning algorithm. In a supervised learning framework, the algorithms try to optimize their performance on unseen data using limited repositories of available data. This is achieved by the theory of generalization while keeping a track of prediction/classification performance. We give a gentle introduction to generalization and predictability followed by demos in R.
6:30 - 7:00 - Mingling and food (sponsored by Blinq Media)
7:00 - 7:05 - Introduction and announcements
7:05 - 8:15 - Talk, demos, Q&A, discussion
8:15 - 8:30 - Hang out