Summer School: Deep Learning and Applications

Upgrade your skills with hands-on deep learning applications

Next edition

12-16 July 2021 (one week).

Applications now open! More info, requirements and enrollment here.

Overview

In this course we will introduce several aspects of modern machine learning, deep learning and it’s applications:

1. An overall introduction to Deep Learning covering convolutional networks, recurrent neural networks, autoencoders and multilayer deep networks. The course includes a 2-hour tutorial on how to code these types of networks using the popular ‘keras’ library for python.
2. Deep Learning for Recommender systems where we deal with the application of advanced Machine Learning and Deep Learning methods in recommender systems. Here we address Tensor Factorization, Factorization Machines, 2vec type embeddings, Deep Collaborative Filtering techniques such as Autoencoders for Collaborative Filtering, RNN’s for session-based recommendations and convolutional networks for feature extraction. This session includes a hands-on part where these techniques are applied to real recommendation data sets using the keras python library.
3. Natural Language Processing with Deep Learning, this module will focus on several aspects of modern NLP such as language modeling, word and document embeddings, conversational models and visualization and the use of Deep Learning models to perform these tasks also including a hands-on session where several of these tasks are coded with keras.
4. The course will also include two data hackathons where the aim will to use the knowledge acquired in the previous days of the summer school.