### Valerio Maggio: _PostDoc Data Scientist @ FBK/MPBA_ ### Contacts:

@leriomaggio

vmaggio@fbk.eu

### Library Versions :::python import keras print('keras: ', keras.__version__) # optional import theano print('Theano: ', theano.__version__) import tensorflow as tf print('Tensorflow: ', tf.__version__) keras: 2.0.2 Theano: 0.9.0 Tensorflow: 1.0.1 ### Outline at a glance - **Part I**: **Introduction to ANN using Tensorflow and Keras** - naive pure-Python implementation - fast forward, sgd, backprop - Model + SGD using Tensorflow - Introduction to Keras main features - `keras.layers.core.Dense` - `keras.backend` - Multi-Layer Perceptron and Fully Connected Networks - **Part II**: **Supervised Learning and Convolutional Neural Nets** - Intro: Focus on Image Classification - Intro to ConvNets - Advanced CNN - Dropout - MaxPooling - Batch Normalisation - Famous Models in Keras (ref: `keras.applications`) - Transfer Learning - **Part III**: **Unsupervised Learning** - AutoEncoders - word2vec & doc2vec (gensim) & `keras.datasets` - `Embedding` - **Part IV**: **Additional Materials** - Recurrent Neural Networks: RNN, LSTM, GRU - HandsOn: IMDB - Multi-Input/Multi-Output Network Topologies