Intro to Text Classification with TensorFlow

Intro to Text
Classification with
TensorFlow

☎Twilio devangelist
😍 ML🤖, APIs
󰜺JS, 🐍
❤ 󰣖, 🎾, 󰝋
…

AI/ML/DL
Some vocabulary
Neural networks
Text Classification 101
Use cases
Performing ML-based
text classification
TensorFlow
Sentiment Analysis w/ TF
Agenda

SECTION TITLE

AI 101
🎓

AI
ML
DL
AI, ML, DL, WTF?
CV NLP

Natural Language Processing: AI
for Words/Language

Some ML Vocabulary

Weak AI
- machine simulates thinking, human
behavior

Strong AI or Artificial General
Intelligence (AGI)
- machine reproduces a human behavior,
thinking

ML Model
Program that can find patterns or make
decisions from a previously unseen dataset

Neural Networks
Mimicking neurons in the human brain,
NNs are a set of algorithms that work to
recognize connections in a dataset

Types of Neural Networks
🧠

Convolutional Neural Network
(CNN)
• classify images, video, text
• fixed-size input + output
• translational invariance
• more powerful
• output = a class the data belongs in
• input = the data itself
•

Recurrent Neural Network (RNN)
• best suited for tasks that require
prediction of the next data
• arbitrary-sized input + output
•

Long Short-Term Memory networks
(LSTM)
• classify text, speech
• arbitrary-sized input + output
•

Text Classification

What is Text Classification?
- intelligent categorization of text, based on
sentiment.
- organize, structure, categorize pretty
much any kind of text – from documents,
medical studies and files, and all over the
web.

Input (text):
I love Disney!
Text
classification
model
Output (tags)

Types of Data?
📀

Characteristics
- predefined data models
- easy to search
- text-based
- shows what
Lives in:
- relational DBs, data warehouses
Stored in:
- rows, columns
-
Structured Data Unstructured Data
Characteristics
- no predefined data models
- tough to search
- text, PDF, images, video
- shows why
Lives in:
- apps, data warehouses/lakes
Stored in:
- various forms
-

Classifier Model

Why is text classification important?
- make most of unstructured data
- save time
- make informed decisions

Use Cases
🕵

Sentiment Analysis
The
product
has been
fantastic!
The
experience
is alright, I
guess
Your
support
team
SUCKS
Positive Neutral Negative
��

Types of Sentiment Analysis
• Polarity of text
Positive
Negative
Neutral
��
��
��
⚠
! ⚠
��
��
• Specific feelings, emotions
• Urgency
• Intention

• Organize articles by topics
• Support 🎫 by urgency, language
• Chat conversations by language
• Brand mentions by sentiment
• Email messages
• Spam filtering
• Prioritizing
• Folderizing

Algorithms to perform ML-based Text
Classification

Naive Bayes
Classification
Algorithm(s)
every pair of features
being classified is
independent of each
other
naive = doesn't consider
correlation between features,
assumes they are independent of
each other

Naive Bayes

Naive Bayes
Multinomial
- discrete data Gaussian
- continuous data
Bernoulli
- binary or boolean values

TensorFlow

- OS library released by Google Brain in
2015
- Image classification, NLP, generate
music, etc.
- Python, JS, Swift, C, etc.
- TF Lite for IoT devices

TensorFlow for sentiment analysis
overview

��

TensorFlow for Sentiment Analysis:
Metadata

Loves Me, Loves me Not: Classify
Texts with TensorFlow and Twilio

Helper libraries for text
classification with TensorFlow

Prepare training data

Stemming vs Lemmatization
adjustable -> adjust. was -> (to) be
formality -> formaliti better -> good
airliner-> airlin. meeting -> meeting
Stemming Lemmatization

Stem🌷 words with TensorFlow

Handle👋
contractions

Read📖 training data

json_data returned ��

Remove duplicates via stemming

Bag-of-words NLP model

Process the numpy array with TF

3-layer Neural network

Deep Neural Network (DNN)

Text📲 +1(863)591-4513

Thank you!
@lizziepika
/elizabethsiegle
https://twil.io/orlandotf

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sed do eiusmod tempor.
get too text heavy
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title in this box
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CUSTOMER STORY

CUSTOMER STORY
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quote. Putting too many
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make it less impactful.
The Brand Team | Twilio
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DECEMBER 2018 JANUARY 2019 FEBRUARY 2019 APRIL 2019
PRODUCT RELEASE TIMELINE

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DECEMBER 2018
JANUARY 2019
FEBRUARY 2019
MARCH 2019
APRIL 2019
Product
release timeline
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STATS AND FIGURES
INCREASE IN
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55%
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65%
95%
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WORLD MAP

VIRGINIA, USA
DUBLIN, IRELAND
SINGAPORE
SYDNEY, AUSTRALIA
TOKYO, JAPAN
SAO PAULO, BRAZIL
DATA CENTERS

OUR CUSTOMERS

OUR EMEA CUSTOMERS

OUR APAC CUSTOMERS

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80%
of the human brain is
made up of water.

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Sean McBride
CREATIVE DIRECTOR
Paul Bustamante
SR. VISUAL DESIGNER
Nathan Sharp
SR. VISUAL DESIGNER
Edmund Boey
VISUAL DESIGNER
DEPARTMENT TITLE

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Intro to Text Classification with TensorFlow

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Intro to Text Classification with TensorFlow