Meandering through the machine learning maze NLP & Machine Learning Vijay Ganti ** I want to acknowledge full credit for the content of this deck to various sources including Stanford NLP & Deep Learning content, Machine Learning Lectures by Andrew Ng, Natural Language Processing with Python and many more. This was purely an educational presentation with no monetary gains for any parties
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Transcript
Meandering through the machine learning maze
NLP & Machine Learning
Vijay Ganti
** I want to acknowledge full credit for the content of this deck to various sources including Stanford NLP & Deep Learning content, Machine Learning Lectures by Andrew Ng, Natural Language Processing with Python and many more. This was purely an educational presentation with no monetary gains for any parties
NLP powered by ML will change the way business gets done
❖ Conversational agents are becoming an important form of human-computer communication (Customer support interactions using chat-bots)
❖ Much of human-human communication is now mediated by computers (Email, Social Media, Messaging)
❖ An enormous amount of knowledge is now available in machine readable form as natural language text (web, proprietary enterprise content)
What do I hope to achieve with this talk?
My 3 cents
Make it accessible & realGet you excitedGive you a sense of what it takes
Make it real
Let’s start with a typical ML workflow
Training Data Feature Extractor ML Algo
Prediction Data Feature Extractor Classifier Model
Features
Features Label
Input + Labels
Input Only
Let’s walk through the workflow with an example
names_data = [(n,'male') for n in names.words('male.txt')]+ [(n,'female') for n in names.words('female.txt')]Training Data