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A BEGINNER’S GUIDE
TO DEEP LEARNING	
Irene Chen	
@irenetrampoline	
PyCon 2016
“A beginner’s guide to
deep learning”
“A beginner’s guide to
deep learning”
Convolutional nets	
Backpropagation	
Image recognition	
Restricted BolNmann machines
DeepMind’s AlphaGo beating
professional Go player Lee Sedol	
Nvidia and its latest GPU architecture	
Toyota’s $1 billion AI investment	
Facebook is building AI that builds AI
Geoff Hinton	
Yann LeCun	
Andrew Ng	
Yoshua Bengio
Too much math	 Too much code
Today	
• Why now?	
• Neural Networks in 7 minutes	
• Deep nets in Caffe
WHY NOW?
Engine (neural
network)
Engine (neural
network)	
Fuel
(data)
Classifier
Classifier	Input	 Output
Classifier	 Ripe?
Classifier	 Ripe?
Trained Classifier	
Ripe?
Logistic regression	
Naïve Bayes	
Support vector machine	
K-nearest neighbors	
Random forests
Trained Classifier	
Ripe?
Lesson 1: Why now? Big
data, big processing power,
robust neural networks
NEURAL NETWORKS IN 7
Photo: Rebecca-Lee (Flickr)
Input Nodes	
Output Nodes
Input Nodes	
Output Nodes
Input Nodes	
Output Nodes
Input Nodes	
Output Nodes	
A	
B
Input Nodes	
Output Nodes	
A	
B	
C
Wikipedia
Input Nodes	
Output Nodes	
A	
B	
C
Input Nodes	
Output Nodes	
A	
B	
C	 D
Input Nodes	
Output Nodes
Input Nodes	
Output
Nodes	
Hidden
layers
Input Nodes	
Output Nodes
Input Nodes	
Output Nodes
Input Nodes	
Output Nodes	
10	
0.5	
200	
4.1
Input Nodes	
Output Nodes	
10	
0.5	
200	
4.1
Input Nodes	
Output Nodes	
10	
0.5	
200	
4.1
Input Nodes	
Output Nodes	
10	
0.5	
200	
4.1
Input Nodes	
Output Nodes	
10	
0.5	
200	
4.1	
95	
17
Forward propagation
Input Nodes	
Output Nodes
Input Nodes	
Output Nodes
Input Nodes	
Output Nodes	
10	
0.5	
200	
4.1
Input Nodes	
Output Nodes	
10	
0.5	
200	
4.1	
95	
17
No randomness!
Input Nodes	
?	
?	
?	
?	
?	
?	
?	
?	
?	
?	
?	
?	
?	?	
?	
Output Nodes
Backpropagation
Input Nodes	
1	
1	
1	
1	
1	
1	
1	
1	
1	
1	
1	
1	
1	1	
1	
Output Nodes
Input Nodes	
Output Nodes	
10	
0.5	
200	
4.1	
1	
1	
1	
1	
1	
1	
1	
1	
1	
1	
1	
1	
1	1	
1
Input Nodes	
Output Nodes	
10	
0.5	
200	
4.1	
1	
1	
1	
1	
1	
1	
1	
1	
1	
1	
1	
1	
1	1	
1
Input Nodes	
Output Nodes	
10	
0.5	
200	
4.1	
1	
1	
1	
1	
1	
1	
1	
1	
1	
1	
1	
1	
1	1	
1
Input Nodes	
Output Nodes	
10	
0.5	
200	
4.1	
1	
1	
1	
1	
1	
1	
1	
1	
1	
1	
1	
1	
1	1	
1
Input Nodes	
Output Nodes	
10	
0.5	
200	
4.1	
4	
20
Input Nodes	
Output Nodes	
10	
0.5	
200	
4.1	
4	
20
Input Nodes	
Output Nodes	
10	
0.5	
200	
4.1	
4	
20
Input Nodes	
Output Nodes	
10	
0.5	
200	
4.1	
5	
19
Values of the nodes	
Amount of error	
Weights of edges	
Learning rate
Input Nodes	
Output Nodes	
10	
0.5	
200	
4.1	
5	
19
Input Nodes	
Output Nodes	
10	
0.5	
200	
4.1	
5	
19
Input Nodes	
Output Nodes	
10	
0.5	
200	
4.1	
5	
19
Input Nodes	
Output Nodes	
10	
0.5	
200	
4.1	
5	
19
Tuning parameters
Input Nodes	
Carlos Xavier Soto	
Output Nodes
Lesson 2: Neural networks
can be trained on labeled
data to classify avocados
DEEP NETS ON CAFFE
Scikit-learn	
Caffe	
Theano	
iPython Notebook
Scikit-learn	
Caffe	
Theano	
iPython Notebook
Loading a pre-trained
network into Caffe
Large Scale Visual
Recognition Challenge 2010
(ILSVRC 2010)
10 million images	
10,000 object classes	
310,000 iterations
Tabby cat	
Tabby cat	
Tiger cat	
Egyptian cat	
Red fox	
Lynx
Lesson 3: Caffe provides
pre-trained networks to
jumpstart learning
Today	
• Lesson 1: Why now? Big data, big
processing power, robust neural
networks	
• Lesson 2: Neural networks can be
trained on labeled data to classify
avocados	
• Lesson 3: Caffe provides pre-trained
networks to jumpstart learning
What do you go from here?
Today	
• Lesson 1: Why now? Big data, big
processing power, robust neural
networks	
• Lesson 2: Neural networks can be
trained on labeled data to classify
avocados	
• Lesson 3: Caffe provides pre-trained
networks to jumpstart learning
Cuda implementations	
Theano, Tensorflow, etc
Today	
• Lesson 1: Why now? Big data, big
processing power, robust neural
networks	
• Lesson 2: Neural networks can be
trained on labeled data to classify
avocados	
• Lesson 3: Caffe provides pre-trained
networks to jumpstart learning
Restricted BolNmann Machines	
Recurrent network	
Convolutional network
Today	
• Lesson 1: Why now? Big data, big
processing power, robust neural
networks	
• Lesson 2: Neural networks can be
trained on labeled data to classify
avocados	
• Lesson 3: Caffe provides pre-trained
networks to jumpstart learning
Caffe iPython notebooks	
Kaggle competitions
Thank you!	
irenetrampoline@gmail.com

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