Hey all, as a company that creates dev tools for AI/ML projects, we spend a ton of time helping our users with the more basic aspects of designing, building, and deploying their applications.
After going through this a few (hundred?) times, we decided to create a guide to machine learning system design and make it available to everyone.
This guide covers the following:
Setting up your machine learning development environment
Preparing, processing and working with machine learning data
Selecting features and predictors for your machine learning model construction
Tools for developing your machine learning system
Utilities for your machine learning system
Testing your machine learning application
Project reproducibility and version control
8.Getting to production
One note, it is gated with just email, as we don't want it scraped
You can access the full guide here https://learning.jozu.com
Top comments (4)
Thank you for this post! This is top client ask today... please clarify best practices..
I liked the explanation, several interesting points. I miss the full content within the post, instead of leaving the page I'm on to see on another platform.
Unfortunately, it's a lot of text (like 15 pages!)
It would be very useful, besides creating 15 new posts, to draw more attention from Dev.To readers.