Presentation at the Google Dev Fest Bari 2016

1. Introduction to Machine
Learning with TensorFlow
Paolo Tomeo

2. Open source Machine Learning library
Especially useful for Deep Learning
For research and production
Apache 2.0 license

3. Machine Learning
Computer algorithms for learning to do something
- learning to complete a task
- make accurate predictions
- to behave intelligently
The focus is on automatic methods: learning without any
human intervention

4. Hello World
Image from https://github.com/mnielsen/neural-networks-and-deep-learning
?

5. What we see What the computer “sees”

6. Complete code
import tensorflow as tf
mnist = tf.contrib.learn.datasets.load_dataset('mnist')
classifier = tf.learn.LinearClassifier(n_classes=10)
classifier.fit(mnist.train.images, mnist.train.labels)
score = metrics.accuracy_score(mnist.test.labels,
classifier.predict(mnist.test.images))
print('Accuracy: {0:f}'.format(score))

8. Biologically Inspired Artificial Neural Network
Image from https://visualstudiomagazine.com/articles/2014/06/01/deep-neural-networks.aspx

9. Deep Neural Network (DNN)

10. Iris Dataset

11. Deep Learning Classifier for Iris Dataset (1/3)
Tutorial from https://www.tensorflow.org/versions/r0.11/tutorials/tflearn/index.html#tf-contrib-learn-quickstart
import tensorflow as tf
import numpy as np
# Data sets
IRIS_TRAINING = "iris_training.csv“
IRIS_TEST = "iris_test.csv"
# Load datasets.
training_set = tf.contrib.learn.datasets.base.load_csv(filename=IRIS_TRAINING,
target_dtype=np.int)
test_set = tf.contrib.learn.datasets.base.load_csv(filename=IRIS_TEST,
target_dtype=np.int)

12. Deep Learning Classifier for Iris Dataset (2/3)
Tutorial from https://www.tensorflow.org/versions/r0.11/tutorials/tflearn/index.html#tf-contrib-learn-quickstart
# Specify that all features have real-value data
feature_columns = [tf.contrib.layers.real_valued_column("", dimension=4)]
# Build 3 layer DNN with 10, 20, 10 units respectively.
classifier = tf.contrib.learn.DNNClassifier(feature_columns=feature_columns,
hidden_units=[10, 20, 10],
n_classes=3,
model_dir="/tmp/iris_model")
# Fit model.
classifier.fit(x=training_set.data,
y=training_set.target,
steps=2000)

13. Deep Learning Classifier for Iris Dataset (3/3)
Tutorial from https://www.tensorflow.org/versions/r0.11/tutorials/tflearn/index.html#tf-contrib-learn-quickstart
# Evaluate accuracy.
accuracy_score = classifier.evaluate(x=test_set.data,
y=test_set.target)["accuracy"]
print('Accuracy: {0:f}'.format(accuracy_score))
# Classify two new flower samples.
new_samples = np.array([[6.4, 3.2, 4.5, 1.5], [5.8, 3.1, 5.0, 1.7]], dtype=float)
y = classifier.predict(new_samples)
print('Predictions: {}'.format(str(y)))

14. Getting Started Exercises

15. Lots of tutorials at tensorflow.org

16. Codelab - goo.gl/xGsB9d Video - goo.gl/B2zYWN
TensorFlow for Poets

17. Mobile TensorFlow

18. Claude Monet - Bouquet of Sunflowers
Images from the Metropolitan Museum of Art (with permission) Image by @random_forests

19. A little more TensorFlow

20. A multidimensional array.
A graph of operations.

21. Data Flow Graphs
Computation is defined as a directed acyclic graph
(DAG) to optimize an objective function
Graph is defined in high-level language (Python)
Graph is compiled and optimized
Graph is executed (in parts or fully) on available low
level devices (CPU, GPU)
Data (tensors) flow through the graph
TensorFlow can compute gradients automatically

22. Architecture
Core in C++
Front ends: Python and C++ today, community may add more
Core TensorFlow Execution System
CPU GPU Android iOS ...
C++ front end Python front end ...

23. tf.contrib.learn
TensorFlow’s high-level machine learning API
Easy to configure, train, and evaluate a variety of machine learning
models
Datasets available in tf.contrib.learn.datasets
Warning: any code in tf.contrib is not officially supported, and may change
or be removed at any time without notice.

24. tf.contrib.learn
TensorFlow’s high-level machine learning API
Easy to configure, train, and evaluate a variety of machine learning
models
Datasets available in tf.contrib.learn.datasets
Warning: any code in tf.contrib is not officially supported, and may change
or be removed at any time without notice.

25. Questions?

26. tensorflow.org
github.com/tensorflow
Want to learn more?
Udacity class on Deep Learning, goo.gl/iHssII
Guides, codelabs, videos
MNIST for Beginners, goo.gl/tx8R2b
TF Learn Quickstart, goo.gl/uiefRn
TensorFlow for Poets, goo.gl/bVjFIL
ML Recipes, goo.gl/KewA03
TensorFlow and Deep Learning without a PhD, goo.gl/pHeXe7
What's Next