Title: An introduction to Deep Learning
Lecturer: Antonio Gullì (Google)
Period: January 2018, 15-19
The goal of this course is to provide an handson introduction to Deep Learning. The traditional concepts used in neural networks are introduced, together with modern convolutional networks, generative adversarial networks, recurrent networks, and autoencoders. In addition, we will look at Reinforcement Learning and its application to AI Game Playing, a popular direction of research and application of neural networks. All the examples will be coded in Keras a python high-level framework running on the top of Google's Tensorflow, Microsoft's CNTK, Amazon's MLXnet, and University of Montreal's theano.