ML engineering is the intersection of machine learning data science and software/systems engineering. It's an emerging field that demands a broad and deep skillset in multiple domains.

Hosted by Garrett Smith at Illinois Institute of Technology

Agenda:
10:00 - 10:45 - Introduction to ML engineering part 1
10:45 - 11:30 - Introduction to ML engineering part 2
11:30 - 12:30 - Coding problem definition
12:30 - 1:00 - Working lunch
1:00 - 3:00 - Coding sessions
3:00 - 4:00 - Show and tell

https://www.meetup.com/Chicago-ML/events/268087380/

I attended the full day hands on workshop at the IIT. The workshop covered the basics and hands on portion had the groups divide up according to the skill level and topics based on the interest. As a result, the pace was kept at a high speed while the teams having opportunity to get support from Garrett. I also recommend checking out the GuildAI which Garrett developed a few years ago. It is fully open source and allows automation of the ML workflow. Thanks for the great session!

Github link below & Other reference material used in the workshop

https://github.com/gar1t/2020-02-15-ml-engineering-at-iit

Get started with GuildAI

https://www-pre.guild.ai/start/

GuildAI Github

https://github.com/guildai/guildai

https://github.com/guildai/guildai/blob/master/examples/notebooks/get-started.ipynb

Recommended group project topics used in the workshop

https://towardsdatascience.com/automated-machine-learning-hyperparameter-tuning-in-python-dfda59b72f8a

https://medium.com/datadriveninvestor/deploy-your-pytorch-model-to-production-f69460192217

https://scikit-learn.org/stable/auto_examples/index.html

Iris Dataset & 2D Iris Dataset