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:

1. Setting up your machine learning development environment

2. Preparing, processing and working with machine learning data

3. Selecting features and predictors for your machine learning model construction

4. Tools for developing your machine learning system

5. Utilities for your machine learning system

6. Testing your machine learning application

7. 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