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https://lena-voita.github.io/nlp_course/transfer_learning.html#main_content
Intro to NLP
How Non-Natural Beings(Computers)
process
Natural Language!
Who’s Me?
- Currently Sr. Data Scientist at Fountain9 (YC’21)
- AI Research enthusiast in the NLP and Time Series
Forecasting domain collaborating with academia.
- Worked at
- Hindustan Coca-Cola Beverage Pvt Ltd,
- then as Solutions Consultant at various co.s including Browserstack
(at the concurrence of technology and business)
- PG Specialisation in Applied DS (Michigan Uni)
B.E. Mechanical Engineering from M.U. (Distinction)
Why Me ?
- 1 PGS, 1 NanoDegree, few internships, some good projects,
50+ paper reviews and 100+ Linkedin courses (because, why
not?)
What is NLP ?
Natural Language Processing is when we program computers to process and analyze large
amounts of natural language data.
What’s natural language data?
Data that we generate on a daily basis by talking, chatting, calling, emailing, commenting……
Limitless data!
NLP is understanding and interpreting this data in a way that a literate human would.
Why NLP?
Why use Natural Language Processing?
- Understand this large amount of data
- Use this large amount of data
- Employ this data to Make models that understand
- Our speech , language, intent, emotion
- And many more endless reasons……
How NLP helps?
- Understand this large amount of data
- Its vibe >> good / bad / neutral >> Sentiment Analysis
- Its meaning
- In simpler words >> Summary
- In different words >> Translation
- Its relation to each other >> Topic Modelling
How NLP Helps?
Eg. 1. Sentiment Scoring
(of a paragraph from a blog on AI )
2. Topic Modelling (of the same blog)
['0.019*"ai" + 0.011*"human" + 0.011*"machine" +
0.007*"intelligence" + 0.007*"learning"']
HOW NLP HELPS?
- Use this large amount of data
- To derive insights
- Regarding opinions >> Discourse analysis
- Regarding objects >> Entity Recognition
- To find answers >> Question Answering
https://course.spacy.io/en/chapter1
Img credits : thecleverprogrammer.com
HOW NLP HELPS?
To build models that
- Understand our commands >> Speech recognition
- Assist us >> Speech to text
- Talk to us >> Text to speech (or basically anything to speech)
How it works?
Preliminary Steps :
- Text Mining
- Frequency, Length, Uniques, Screening for X/Y
- Text Analytics
- Patterns, Structures, Combinations, Network Graphs
How IT Works?
Examples : WordCloud & Word Network Graphs
Credits: online.une.edu,
How it works?
Word Embeddings
bUT HOW DOES IT ACTUALLY HELP?
Like , for real!!!
Here’s 2 good cases that apply universally(regardless of
domain).
Subject : ABC has partnered with us for
‘xyz’.
Subject : Domain leaders are leveraging
‘xyz’, are you?
Body : Word pairs, cloud, summarisation
Do you have a Knowledge Base ?
Is it Indexed? Tree-mapped ? Flowy?
Why Buy a Chatbot,
when you can Build it! :p
What’s More ?
Recurrent Neural Networks
Sequence to Sequence
Rise of Attention Layers
Self-Attention
Transformers - Multi Headed self attention
BERT (MLM NSP)
Stanford’s SQuAD

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Agile Mumbai 2022 - Vikesh Morye | Transfer Learning for Business Agility

  • 1.
  • 3.
  • 4. Intro to NLP How Non-Natural Beings(Computers) process Natural Language!
  • 5. Who’s Me? - Currently Sr. Data Scientist at Fountain9 (YC’21) - AI Research enthusiast in the NLP and Time Series Forecasting domain collaborating with academia. - Worked at - Hindustan Coca-Cola Beverage Pvt Ltd, - then as Solutions Consultant at various co.s including Browserstack (at the concurrence of technology and business) - PG Specialisation in Applied DS (Michigan Uni) B.E. Mechanical Engineering from M.U. (Distinction) Why Me ? - 1 PGS, 1 NanoDegree, few internships, some good projects, 50+ paper reviews and 100+ Linkedin courses (because, why not?)
  • 6. What is NLP ? Natural Language Processing is when we program computers to process and analyze large amounts of natural language data. What’s natural language data? Data that we generate on a daily basis by talking, chatting, calling, emailing, commenting…… Limitless data! NLP is understanding and interpreting this data in a way that a literate human would.
  • 7. Why NLP? Why use Natural Language Processing? - Understand this large amount of data - Use this large amount of data - Employ this data to Make models that understand - Our speech , language, intent, emotion - And many more endless reasons……
  • 8. How NLP helps? - Understand this large amount of data - Its vibe >> good / bad / neutral >> Sentiment Analysis - Its meaning - In simpler words >> Summary - In different words >> Translation - Its relation to each other >> Topic Modelling
  • 9. How NLP Helps? Eg. 1. Sentiment Scoring (of a paragraph from a blog on AI ) 2. Topic Modelling (of the same blog) ['0.019*"ai" + 0.011*"human" + 0.011*"machine" + 0.007*"intelligence" + 0.007*"learning"']
  • 10. HOW NLP HELPS? - Use this large amount of data - To derive insights - Regarding opinions >> Discourse analysis - Regarding objects >> Entity Recognition - To find answers >> Question Answering https://course.spacy.io/en/chapter1 Img credits : thecleverprogrammer.com
  • 11. HOW NLP HELPS? To build models that - Understand our commands >> Speech recognition - Assist us >> Speech to text - Talk to us >> Text to speech (or basically anything to speech)
  • 12. How it works? Preliminary Steps : - Text Mining - Frequency, Length, Uniques, Screening for X/Y - Text Analytics - Patterns, Structures, Combinations, Network Graphs
  • 13. How IT Works? Examples : WordCloud & Word Network Graphs Credits: online.une.edu,
  • 14. How it works? Word Embeddings
  • 15.
  • 16. bUT HOW DOES IT ACTUALLY HELP? Like , for real!!! Here’s 2 good cases that apply universally(regardless of domain).
  • 17. Subject : ABC has partnered with us for ‘xyz’. Subject : Domain leaders are leveraging ‘xyz’, are you? Body : Word pairs, cloud, summarisation
  • 18.
  • 19. Do you have a Knowledge Base ? Is it Indexed? Tree-mapped ? Flowy? Why Buy a Chatbot, when you can Build it! :p
  • 20.
  • 21.
  • 22. What’s More ? Recurrent Neural Networks Sequence to Sequence Rise of Attention Layers Self-Attention Transformers - Multi Headed self attention BERT (MLM NSP) Stanford’s SQuAD