Machine learning problems are solved around the world - but there are many ways to start, execute, and finish a project like this, and it is hard to keep up with a fast pacing field like this.
Our goal is to collect and document different approaches to solve real-world machine learning tasks, for professionals and beginners alike. These may be steps applied before, during, and after solving a particular problem and aims to answer questions like:
- What are the ways to deploy models?
- Which neural network architecture should I try first?
- What is GDPR compliance of a model and how to achieve it?
We would love if you could share your knowledge with us, especially if you feel like there is something missing, outdated, or flat out wrong. Spelling is valid too!
In order to help, read the texts, open issues or check out existing issues and see if you can help out.
GPLv3