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Modern Practical Natural Language Processing

This course will cover how you can use NLP to do stuff.

There are four videos

For translation and document summarization, and for pulling out sentences and documents that talk about specific things
"I need every mention of a street address or business in Garland, Texas; and I need each document translated to Urdu."
Video

The idea is we make short videos that focus on the aspects of NLP that currently work well and are useful.

Speech-to-text now works pretty well, so these methods will also be useful for the audio portions of videos.

PhD in Computer Science in 2010 from UT Austin
Thesis work was about how a robot could wake up in the world and figure out what is going on
Work at DeUmbra where we build AI for the DoD
- We also work in healthcare, which I can talk about. A future video (not in this series) will cover how we use graph neural networks to identify who is at risk for opioid overdose
- Hands-on technical advisor at our sister company Pulselight
Wrote The Curiosity Cycle: Preparing Your Child for the Ongoing Technological Explosion
Advisor at KUNGFU.AI
Also do independent consulting work
Can find me here jonathanwilliammugan@gmail.com or on Twitter at @jmugan

Reading requires mapping language to internal concepts grounded in behaving in the same general environment as the writer.
- Computers don’t have those concepts.
- Example: “I pulled the wagon.” Computers don’t know that wagons can carry things or that pulling exerts a gentle tension to the arm and leg muscles as one walks.

Writing requires mapping internal concepts grounded in behaving in the same general environment as the expected reader.
- Computers don’t have those concepts

NLP is about how to make natural language amenable to computation even though computers can’t read or write.
Representing text as vectors has transformed NLP in the last 10 years.
There are also symbolic methods that are practically useful; we will cover those too.