Maybe the template will make it easier for you to start putting together a doc:
1️⃣ Create a scheme of the main development stages adopted in your team, for example:
• task setting;
• data exploration;
• formulating the task in ML terms;
• MVP solution;
• testing the solution;
• rolling it out to production;
• monitoring.
2️⃣ Describe each stage:
• what needs to be done;
• what the result should look like to proceed to the next step.
Try to avoid long texts; use diagrams, tables, infographics.
3️⃣ Add to each stage:
• templates that will allow you to complete this stage faster;
• useful tips;
• standards and requirements, if any;
• links to resources, articles, documents that can help at this stage;
• answers to popular questions;
• documentation requirements: what and where needs to be described to consider the stage completed.
After putting together the ML process, don't forget to request feedback from colleagues who didn't participate in its development. And also inform everyone interested about the appearance of a new useful tool.
And remember, the ML process can't be written once. The practices adopted in the company change, new tools appear to replace or supplement the old ones, versions are updated. It's important to regularly keep your ML process up to date and adapt it to new needs.
It's not you who adapt to the process, but the process that adapts to you!
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🤖 Data & ML | @DataXplore