In this episode of Elixir Wizards, Katelynn Burns, software engineer at LaunchScout, and Alexis Carpenter, senior data scientist at cars.com, join Host Dan Ivovich to discuss machine learning with Elixir, Python, SQL, and MATLAB. They compare notes on available tools, preprocessing, working with pre-trained models, and training models for specific jobs.
The discussion inspires collaboration and learning across communities while revealing the foundational aspects of ML, such as understanding data and asking the right questions to solve problems effectively.
Topics discussed:
Using pre-trained models in Bumblebee for Elixir projects
Training models using Python and SQL
The importance of data preprocessing before building models
Popular tools used for machine learning in different languages
Getting started with ML by picking a personal project topic of interest
Resources for ML aspirants, such as online courses, tutorials, and books
The potential for Elixir to train more customized models in the future
Similarities between ML approaches in different languages
Collaboration opportunities across programming communities
Choosing the right ML approach for the problem you're trying to solve
Productionalizing models like fine-tuned LLM's
The need for hands-on practice for learning ML skills
Continued maturation of tools like Bumblebee in Elixir
Katelynn's upcoming CodeBeam talk on advanced motion tracking
Links mentioned in this episode
https://launchscout.com/
https://www.cars.com/
Genetic Algorithms in Elixir (https://pragprog.com/titles/smgaelixir/genetic-algorithms-in-elixir/) by Sean Moriarity
Machine Learning in Elixir (https://pragprog.com/titles/smelixir/machine-learning-in-elixir/) by Sean Moriarity
https://github.com/elixir-nx/bumblebee
https://github.com/huggingface
https://www.docker.com/products/docker-hub/
Programming with MATLAB (https://www.mathworks.com/products/matlab/programming-with-matlab.html)
https://elixirforum.com/
https://pypi.org/project/pyspark/ 
Machine Learning Course (https://online.stanford.edu/courses/cs229-machine-learning) from Stanford School of Engineering
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow (https://www.oreilly.com/library/view/hands-on-machine-learning/9781492032632/) by Aurélien Géron
Data Science for Business (https://data-science-for-biz.com/) by Foster Provost & Tom Fawcett
https://medium.com/@carscomtech 
https://github.com/k-burns 
Code Beam America (https://codebeamamerica.com/) March, 2024
Special Guests: Alexis Carpenter and Katelynn Burns.