Genetic Algorithms in Elixir • Sean Moriarity & Bruce Tate

GOTO - Today, Tomorrow and the Future

This interview was recorded for the GOTO Book Club.
gotopia.tech/bookclub

Read the full transcription of the interview here
Sean Moriarity - Author of "Genetic Algorithms in Elixir" & "Machine Learning in Elixir" Bruce Tate - President at Groxio & Author of many Books
RESOURCES
Sean
seanmoriarity.com
@sean_moriarity
github.com/seanmor5
Bruce
grox.io
@redrapids
linkedin.com/in/bruce-tate

DESCRIPTION
From finance to artificial intelligence, genetic algorithms are a powerful tool with a wide array of applications. But you don’t need an exotic new language or framework to get started; you can learn about genetic algorithms in a language you’re already familiar with. Join us for an in-depth look at the algorithms, techniques, and methods that go into writing a genetic algorithm. From introductory problems to real-world applications, you’ll learn the underlying principles of problem solving using genetic algorithms.
* Book description: © The Pragmatic Bookshelf
The interview is based on the book "Genetic Algorithms in Elixir"
RECOMMENDED BOOKS
Sean Moriarity • Genetic Algorithms in Elixir
Sean Moriarity • Machine Learning in Elixir
Bruce Tate • Programmer Passport: Elixir
Bruce Tate • Programmer Passport: Prolog
Bruce Tate, Ian Dees, Frederic Daoud & Jack Moffitt • Seven More Languages in Seven Weeks
Bruce Tate • Seven Languages in Seven Weeks
Svilen Gospodinov • Concurrent Data Processing in Elixir
Ian Goodfellow, Yoshua Bengio & Aaron Courville • Deep Learning
Francois Chollet • Deep Learning with Python

Twitter
Instagram
LinkedIn
Facebook
Looking for a unique learning experience?
Attend the next GOTO conference near you! Get your ticket: gotopia.tech
SUBSCRIBE TO OUR YOUTUBE CHANNEL - new videos posted daily!

Chapters

1. Intro (00:00:00)

2. Is Elixir a good language for ML? (00:01:31)

3. Numerical Elixir (Nx) (00:04:54)

4. The potential of Elixir & ML together (00:11:20)

5. Use cases for the Bumblebee library (00:23:44)

6. Why is Elixir a good fit for ML? (00:26:18)

7. Behind-the-scenes stories (00:31:40)

8. Pitching Elixir for ML (00:38:11)

9. What's next? (00:39:35)

10. Outro (00:41:06)