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Keras Tutorial @ Web Valley 2017

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@leriomaggio leriomaggio released this 22 Aug 13:13
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Deep Learning with Keras and Tensorflow

WebValley 2017 Logo

Valerio Maggio: PostDoc Data Scientist @ FBK/MPBA

Contacts:

@leriomaggio vmaggio@fbk.eu

Installed Versions

import keras
print('keras: ', keras.__version__)

# optional
import theano
print('Theano: ', theano.__version__)

import tensorflow as tf
print('Tensorflow: ', tf.__version__)
keras:  2.0.4
Theano:  0.9.0
Tensorflow:  1.2.1

Outline

  • Part I: Introduction

    • Intro to Artificial Neural Networks

      • Perceptron and MLP
      • naive pure-Python implementation
      • fast forward, sgd, backprop
    • Introduction to Deep Learning Frameworks

      • Intro to Theano
      • Intro to Tensorflow
      • Intro to Keras
        • Overview and main features
        • Overview of the core layers
        • Multi-Layer Perceptron and Fully Connected
          • Examples with keras.models.Sequential and Dense
        • Keras Backend
  • Part II: Supervised Learning

    • Fully Connected Networks and Embeddings

      • Intro to MNIST Dataset
      • Hidden Leayer Representation and Embeddings
    • Convolutional Neural Networks

      • meaning of convolutional filters

        • examples from ImageNet
      • Visualising ConvNets

      • Advanced CNN

        • Dropout
        • MaxPooling
        • Batch Normalisation
      • HandsOn: MNIST Dataset

        • FC and MNIST
        • CNN and MNIST
      • Deep Convolutiona Neural Networks with Keras (ref: keras.applications)

        • VGG16
        • VGG19
        • ResNet50
    • Transfer Learning and FineTuning

    • Hyperparameters Optimisation

  • Part III: Unsupervised Learning

    • AutoEncoders and Embeddings
    • AutoEncoders and MNIST
      • word2vec and doc2vec (gensim) with keras.datasets
      • word2vec and CNN
  • Part IV: Recurrent Neural Networks

    • Recurrent Neural Network in Keras
      • SimpleRNN, LSTM, GRU
    • LSTM for Sentence Generation
  • PartV: Additional Materials:

    • Custom Layers in Keras
    • Multi modal Network Topologies with Keras