SlideShare a Scribd company logo
WHAT YOU SEE
IS WHAT WE GET
Deep Learning for
Natural Language
Processing
About me...
2
GumGum Inc
3
Artificial Intelligence Company
9 year old, 225 Employees
Based in Santa Monica, CA
Offices in London, Sydney, New York,
Chicago
Thousands of Publishers and Advertisers
Billions of Impressions per day
GumGum Inc: Advertisement
4
GumGum Inc: Sports
5
Topics
6
General Understanding
Word Embedding
Sentences
Paragraphs
Tensorflow
Brain’s interpretation...
7
Hi, what’s up?
Hi, how are you?
Trying to understand DL!
Mr. Cool Brain
Brain’s mapping to Deep Learning
8
USC is the oldest private
research university in
California.
USCFight On!!
0.58 1.60 0.10 -0.85 -0.18 -0.97 -0.14 1.22 1.89 1.91 0.78 0.33 -0.66 -0.19 1.59
Embeddings
Deep Learning in NLP...
9
Machine Learning
Bags of
n-grams
Index
Weight
Deep Learning
Word
Sequence
Vector
Index
Word Embeddings
10
Word Embeddings : Word2Vec
11
CBOW
PROJECTIONS
in
speak
French
France
When
OUTPUTINPUTS
Word Embeddings : Word2Vec
12
Skip-gram
PROJECTIONS OUTPUT
in
speak
French
When
France
INPUTS
Word Embeddings : Glove
13
https://nlp.stanford.edu/projects/glove/
Co-occurrence Matrix
Sentences
14
I like playing soccer
-7.76 -0.28 -4.12 -1.67 -5.02
x
-6.97 -9.9 -1.94 -0.03 -5.19 -6.66 9.84 -5.44 -3.38 -8.06 -7.54 -8.74 -6.46 -9.61 -3.70-9.87 7.68 -2.66 6.35 -1.49
Sentences : Recurrent Neural Network (RNN)
15
x
RNN
y1
Sentences : Recurrent Neural Network (RNN)
16
I
RNN
y1
x1
h1
WX
Wh
Wo
INPUT
HIDDEN
OUTPUT
i1
= Wx
x1
h0
Wh
h0
h1
= tanh( i1
+ Wh
h0
)
y1
= ( Wo
h1
)
Sentences : Recurrent Neural Network (RNN)
17
I like playing soccer
RNN RNN RNN RNN
y1
y2
y3
y4
x1
x2
x3
x4
h1
h2
h3
h4
WX
WX
WX
WX
Wh
Wh
Wh
Wo
Wo
Wo
Wo
h0
Wh
Sentences : RNN : Long Short Term Memory (LSTM)
18
x
LSTM
y1
I
LSTM
y1
x1
h1
WX
Wh
Wo
h0
LSTM
Sentences : RNN : Long Short Term Memory (LSTM)
19
xt
tanh
tanh
ht
Ct
Ct-1
ht-1
Sentences : RNN : Long Short Term Memory (LSTM)
20
xt
tanh
tanh
ht
Ct
Ct-1
ht-1
forget gate
ft
ft
= ( Wxf
xt
+ Whf
ht-1
)
Whf
Wxf
Sentences : RNN : Long Short Term Memory (LSTM)
21
xt
tanh
tanh
ht
Ct
Ct-1
ht-1
input gate
ft
it
= ( Wxi
xt
+ Whi
ht-1
)
Whf
Wxf
Whi
Wxi
it
Ct
~
Whc
Wxc
= tanh ( Wxc
xt
+ Whc
ht-1
)Ct
~
Sentences : RNN : Long Short Term Memory (LSTM)
22
xt
tanh
tanh
ht
Ct
Ct-1
ht-1
cell state update
ft
Whf
Wxf
Whi
Wxi
it
Ct
~
Whc
Wxc
Ct
= ft
* Ct-1
+ it
*Ct
~
Sentences : RNN : Long Short Term Memory (LSTM)
23
xt
tanh
tanh
ht
Ct
Ct-1
ht-1
output gate
ft
Whf
Wxf
Whi
Wxi
it
Ct
~
Whc
Wxc
ot
= ( Wxo
xt
+ Who
ht-1
)
Who
Wxo
ht
= ot
* tanh( Ct
)
ot
GRU
Sentences : RNN : Gated Recurrent Unit (GRU)
24
xt
ht
ht-1
1 -
zt
tanh
rt
zt
= ( Wxz
xt
+ Whz
ht-1
)
rt
= ( Wxr
xt
+ Whr
ht-1
)
ct
= tanh( Wxc
xt
+ Whc
( rt
* ht-1
) )
ht
= (1 - zt
) * ht-1
+ zt
* ct
Whz Wxz
Whr
Wxr
Whc
Wxc
ct
Sentences : Convolutional Neural Network (CNN)
25
I like playing soccer
-5.75 -0.59 2.32 -8.76 -8.12
Wl1
Wr1
Wl1
Wr1
Wl1
Wr1
Wl2
Wr2
Wl2
Wr2
Wl3
Wr3
Paragraphs
26
I like playing soccer . I wish I was any good though .
RNN RNN
y
h0
h13
h5
RNN RNN
h6
Paragraphs
27
I like playing soccer . I wish I was any good though .
RNN RNN
h0
h8
h5
RNN RNN
h1
y
RNN RNN
h0
h0
h1
h2
Classification Task
28
I
like
playing
soccer
.
I
wish
I
was
any
good
.
LSTM
LSTM
LSTM
LSTM
LSTM
LSTM
LSTM
LSTM
LSTM
LSTM
LSTM
LSTM
ATTENTION LSTM
LSTMATTENTION
ATTENTION SOFTMAX
Hierarchical Attention Networks for Document Classification
https://www.cs.cmu.edu/~diyiy/docs/naacl16.pdf
Tensorflow: Workflow
30
Train Data Embedding Layer
xy
Ops
Loss
Gradients
Batch
Predictions
Updates
word2idx
tag2idx
Tensorflow: CODE!!!!
31
Part of Speech Tagging using Recurrent Neural Networks
https://github.com/roopalgarg/recurrent-neural-nets-tensorflow
Other Frameworks
32
Reading material...
33
● http://karpathy.github.io/2015/05/21/rnn-effectiveness
● http://colah.github.io/posts/2015-08-Understanding-LSTMs
● http://www.wildml.com/2016/08/rnns-in-tensorflow-a-practical-guide-and-undocumented
-features/
● http://www.wildml.com/2015/11/understanding-convolutional-neural-networks-for-nlp
● http://www.wildml.com/category/nlp/
● http://www.wildml.com/2016/01/attention-and-memory-in-deep-learning-and-nlp/
● http://www.wildml.com/2015/12/implementing-a-cnn-for-text-classification-in-tensorflow/
Courses:
● DL for NLP: http://cs224d.stanford.edu
● Udacity Deep Learning: https://classroom.udacity.com/courses/ud730
THANK YOU!
Roopal Garg
roopal@gumgum.com
roopalgarg
@roopalgarg

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