13 Tereshchenkivska, office 110
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Starting time is 20:00 !!!
Title: Deep Learning Theory
Abstract: Although neural networks have long been considered lacking in theory and much remains to be done, theoretical evidence is mounting and will be discussed, to support distributed representations, depth of representation, the non-convexity of the training objective, and the probabilistic interpretation of learning algorithms (especially of the auto-encoder type, which were lacking one). The talk will focus on the intuitions behind these theoretical results.
Live from Paris Machine Learning Meetup
Title: Classifying plankton with deep neural networks
Deep learning has become a very popular approach for solving computer vision problems in recent years. In this talk we'll demonstrate how this approach can be applied in practice. We'll show how our team of 7 built a model for the automated classification of plankton based on convolutional neural networks. Using this model, we placed 1st in the National Data Science Bowl competition on Kaggle.
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