Evaluating and developing machine learning models: äN introduction
An introduction to evaluating machine learning models, with an encouragement to develope and research them. Why and how to start (even without a powerful GPU), where to orient, what challenges exist and how to overcome or avoid them.
While this presentation will cover material for beginners, especially the open questions and dialog at the end will be interesting for seasoned researchers as well.
This presentation will cover the following topics:
- Motivation to start evaluating (and developing) machine learning models
- Open research questions
- Current research limitations
- How to start your first project
- Project approaches
- Challenges
- Common mistakes
- Tips when using python and pytorch
- Resources for information and code
Licensed to the public under https://creativecommons.org/licenses/by/4.0/