1. Introduction to Machine Learning and NLP

2. Agenda Max McCann Phillipe Loher Q&A Applications of NLP
Brief History of Machine Learning
Current Industry Leaders
Phillipe Loher
NLP Component – Word Representations
Q&A

3. So Why Natural Language Processing?
Making computers more accessible
Allow more natural human interaction
Find insights from unstructured/semi-structured data

4. A Brief History of Machine Learning
“A computer would deserve to be called intelligent if it could deceive a human into believing that it was human” – Alan Turing

5. Alan Turing Computing Machinery and Intelligence, 1950
Father of CS and AI
Turing Test

6. The Georgetown Experiment 1954
Translate 60 Russian Sentences
Received as a Success in 1954
3-5 Years Est. Translation Solved
Funding Cut After 10

7. Time Line Golden Years 1956 – 1974 First AI Winter 1974 – 1980
AI Boom – 1987
Second Winter 1987 – 1993

8. 1993 to Present Day Deep Blue Beats Chess Master 1993 Jabberwacky 1997
Cleverbot 59.3% Human
Watson on Jeopardy
Alphago Beats Lee Sedol in Go
SyntaxNet, World’s Most Accurate Parser May
Whitehouse Response to AI Oct

9. Home Automation Via NLP

10. Giants Chasing Unicorns

12. NLP Applications
“If you’ve got a computer that can play Go…then there could be an algorithm that said, Go penetrate the nuclear codes and figure out how to launch some missiles.” – President Obama

13. What can be done with NL? NL Parsing NL Understanding NL Generation
Tokenization, Splitting text into sentences
NL Understanding
Text context, keywords, summarization, QA
NL Generation
Speech/Character Recognition

14. More Applications Part-of-speech Tagging Parsing Question Answering
Reference Resolution
Discourse Analysis
Machine Translation
Morphological Segmentation
Named Entity Recognition
Natural Language Generation
Natural Language Understanding
Word sense disambiguation
Information Retrieval/Extraction
Speech Processing
Part-of-speech Tagging
Parsing
Question Answering
Relationship Extraction
Sentence Breaking
Sentiment Analysis
Speech Segmentation
Topic Segmentation
Word Segmentation

16. Questions

17. Resources
artificial-intelligence
processing/