Deep learning with tensorflow 1/2 & 2/2

Since 2012, deep neural networks have led to outstanding results in various applications, literally exceeding any previously existing methods, in texts, images, sounds, videos, graphs… They consist of a cascade of parametrized linear and non-linear operators whose parameters are optimized to achieve a fixed task. This tutorial will first propose a brief introduction to the solved problems and how to design such neural networks. In a second step, notebooks will be proposed in tensorflow/keras.