Unlock NER for Sensitive Data with NLOP - GDSC 2023

Today we’re going to learn about Natural Language Processing. NLP is a technology that teaches machines to understand human languages.
Specifically…we will learn how to use an NLP model to teach a machine to recognize when a human shares potentially sensitive information in a consumer or enterprise system.

Transcript

1. NLP for Sensitive Data
   NORP
   DATE
   ORG
   GPE
   MONEY
   GPE
   PERSON QUANTITY
   Noble Ackerson
   Applied AI Product Lead,
   Former Google Developers Expert for Product Strategy
   Sensitive Text Detection with Custom Natural
   Language Processing (NLP) Models
   

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2. Agenda
   1 Demo: Custom Entity Recogniser
   Process
   Real world use-cases
   2
   3
   

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3. Demo
   Custom Named Entity Recogniser
   

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4. What is Natural Language Processing (NLP)?
   Input
   ❏ Natural Language
   ❏ Text
   ❏ Speech
   Output
   ❏ General text classification
   ❏ Entity extraction
   ❏ Machine translation
   ❏ Question and Answering
   ❏ Embeddings & Semantic Search
   ❏ Conversational machine interaction
   ❏ …
   Process
   ❏ Text representation
   ❏ Machine Learning Models
   ❏ Generative
   ❏ Semantic meaning
   ❏ Contextual understanding
   Generative AI (NLU with LLMs)
   

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5. Process
   1 Identifying the right NLP Use Cases
   Annotate data with the help of Generative AI
   Train a custom Named Entity Recognition (NER) model & refine
   Evaluate, test, custom NER model
   Deploy and integrate
   2
   3
   4
   5
   
   Today’s Tools
   ● Google Colab (shared)
   ● spaCy NLP library
   ● Google Cloud Platform
   

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6. Identifying the right NLP Use Cases
   Human-centered needs analysis for A.I.
   Don’t “A.I.”
   all the things.
   

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7. Identifying the right NLP Use Cases
   User patterns Scope
   

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8. Production grade ML/NLP
   DATA
   MANAGEMENT
   DATA
   COLLECTION
   EXPLORATION &
   ANALYSIS TOOLS
   NLP
   CODE
   FEATURE
   ENGINEERING
   (Labeling, Annotations)
   MODEL TRAINING
   AT SCALE
   AUTOMATION
   LOGGING &
   MANAGEMENT
   MONITORING
   SERVING
   INFRASTRUCTURE
   NEEDS
   ANALYSIS
   Adapted from: “Hidden Technical Debt in Machine Learning Systems”, D. Sculley et. al, Google
   

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9. Identifying the right NLP Use Cases
   Automation Augmentation
   User doesn’t know how to do something User feels responsible for task
   User can’t do something High stakes situation
   Task is boring, repetitive, or dangerous Complicated personal preferences
   If Machine Learning and NLP is needed, which type is best?
   

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10. Setting expectations
    NLP
    CODE
    DATA
    MANAGEMENT
    DATA
    COLLECTION
    EXPLORATION &
    ANALYSIS TOOLS
    

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11. Process
    1 Identifying the right NLP Use Cases
    Annotate data with the help of Generative AI
    Train a custom NER model & refine
    Evaluate, test, custom NER model
    Deploy and integrate
    2
    3
    4
    5
    
    

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12. Annotating your
    text for
    Entity Recognition
    Labeling
    

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13. Teacher: Class, pay attention
    Transformer Models:
    A brief bit about how
    NLU, LLM, GenAI
    play into NER workflow
    Deep
    Learning
    Machine
    Learning
    Natural
    Language
    Processing
    (NLP)
    Large
    Language
    Models
    (LLM)
    Artificial
    Intelligence
    

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14. Process
    1 Identifying the right NLP Use Cases
    Annotate data with the help of Generative AI
    Train a custom NER model & refine
    Evaluate, test, custom NER model
    Deploy and integrate
    2
    3
    4
    5
    
    

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15. The NLP workflow
    for training custom
    Entity Recognition
    …with Large Language Models
    

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16. Starting with
    Pre-trained
    NER Models
    

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17. Process
    1 Identifying the right NLP Use Cases
    Annotate data with the help of Generative AI
    Train a custom NER model & refine
    Evaluate, test, custom NER model
    Deploy and integrate
    2
    3
    4
    5
    
    

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20. Wrap up
    1 Demo: Custom Entity Recogniser
    Process
    Real world use-cases
    2
    3
    

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21. Healthcare
    Clinical
    Documentation
    Custom Entities for Clinical Documentation
    NORP
    DISEASE
    CONDITION
    GPE
    DOSAGES
    PERSON
    MEDICATION EHR
    

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22. Legal
    Contract
    Analysis
    Custom Entities for Legal Documents
    RIGHTS
    CLAUSE
    CONDITION
    GPE
    JURISDICTION
    PARTIES
    CONTRACT DATE
    

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23. Sentiment
    Analysis
    Use Case
    cloud.google.com/natural-language
    

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24. Translation
    Use Case
    https://cloud.google.com/translate
    

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25. All-industries
    Try Natural
    Language AI on
    Google Cloud
    cloud.google.com/natural-language
    

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26. Good luck and
    Thank you!
    Noble Ackerson
    AI Product Lead, GDE Alumni
    medium.com/@nobleackerson
    youtube.com/c/nobleackerson
    Resources
    What is Natural Language Processing? [Google Cloud]
    Natural Language Processing on Google Cloud [Cloud Skills Boost]
    TensorFlow Models NLP Library [tensorflow.org]
    

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27. Identifying Use Cases for LLMs
    Risk Tolerance Human Review Text (or Code) Intensive Business Value
    

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28. Token Classification with Custom NER models
    Inputs
    Training &
    Validation
    Datasets
    Deploy
    API and
    Versioning
    Prediction
    Clients
    (Online Systems)
    REST API call with
    input variables
    Trained
    Models
    Training
    Serving
    Preprocess
    & Feature
    Creation
    Preprocess
    Labeling &
    Annotation
    Train/Tune
    Model
    

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29. In case of demo fail
    

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