Practical TensorFlowIllia Polosukhin, Google Research@ilblackdragon

Why Machine Learning?

★ Allows to solve problems we don’t have exact solution for.○ E.g. recommendations, predictions, clustering.

★ Given y = F(X), where we observe y, we can estimate F.

★ Becomes better with more data ○ when hard coded solution usually becomes worse with more

code :)

Google Products Using Machine Learning

Big Data Challenges

★Variety of data★Learning many things at once★Small data where matters

Deep LearningInput

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Deep Learning for Perception Tasks

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Deep Learning for Perception Tasks

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Deep Learning for Perception Tasks

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Deep Learning for Perception Tasks

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Deep Learning for Perception Tasks

Deep Learning combines many components

Predictions

GoogLeNet

Recurrent Neural Network

Deep Learning: Leverage pre-training

What is TensorFlow?

TensorFlow Ecosystem

Researchers Developers

Data Scientists

TensorFlow Core Execution Engine

CPU GPU Android iOS ...

C++ FrontendPython Frontend ...

TensorFlow: Google backed

★ Google supported (growing army of engineers are working on improving it).

★ Used in 100s of products across Google

How can I use this?

TensorFlow Learn

Simple example:

How can I use this?

Predictive Example

Going to deep neural network is easy:

Understanding Images

Image Classification

Recommendation Example

Recommendation Example

Image Description Item User

N layers of convolutions RNN encoder Item

embeddingsUser

embeddings

Concatenate

N fully connected layers Item embeddings P(item)

Scaling Out

TensorFlow scales with number of Machines.

You can use Google Cloud ML or Docker containers in VMs.https://arxiv.org/abs/1604.00981

TensorFlow Serving: Serving models in production

Open Source project.

Check it out:

http://github.com/tensorflow/serving

Questions?

Illia Polosukhin@ilblackdragon

#TensorFlowhttp://github.com/tensorflow/tensorflow

http://tensorflow.org