The document summarizes the agenda for the TensorFlow Dev Summit in Rome 2017. It includes sessions on the history and breakthroughs of TensorFlow over the past year, a keynote presentation, and networking. Additional topics discussed include backpropagation, inception models, using TensorFlow for symbolic models and automatic gradient computation, an example of creating a simple Keras model in TensorFlow, neural image captioning, neural machine translation, generative adversarial networks, AlphaGo, WaveNet, and ways to get involved in future events.

1. TensorFlow Dev Summit Ext Roma 2017
16 Febbraio 2017, Talent Garden - Cinecittà

2. Agenda
18:40-19:00 TensorFlow: one year of exciting
breakthroughs (Simone Scardapane)
19:00-20:30 Keynote streaming
20:30-21:30 Networking

3. Backpropagation
Backpropagation: how it works [YouTube]

4. Inception
Gooing Deeper Into Convolutions [Google Research Blog]

5. TensorFlow
Symbolic model definition
Automatic gradient computation
Efficient CPU/GPU computations

6. An example (with Keras)
Create a simple model with two layers:
model = Sequential()
model.add(Dense(20, input_dim=16, init='uniform', activation='relu'))
model.add(Dense(1, init='uniform', activation='sigmoid'))
model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])
model.fit(X, Y, nb_epoch=50, batch_size=100)
Train the model:

7. Neural Image Captioning
Download TensorFlow Code

8. Neural Image Captioning (2)
Source: GitHub Repository

9. Neural Machine Translation
A Neural Network for Machine Translation, at Production Scale

10. Neural Machine Translation (2)
A Neural Network for Machine Translation, at Production Scale

11. Generative Adversarial Networks
An introduction to Generative Adversarial Networks (with code in TensorFlow)

12. AlphaGo
How AlphaGo Mastered the Game of Go with Deep Neural Networks

13. WaveNet
WaveNet: A Generative Model for Raw Audio

14. Get involved
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• Eventi
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• Laboratori
• Talk