Evaluating, comparing, and selecting ML models
Contents
Evaluating, comparing, and selecting ML models#
Welcome to the fifth lecture of the STRV Data Science Academy. After the previous four lectures, you should have some idea about how to get the data for your ML project and what algorithms are there to work with the data. But how to select the correct algorithm for your problem? And how to parametrize it the best way? This lecture should give you the answers.
The Plan#
Section |
Time |
|---|---|
10 minutes |
|
50 minutes |
|
Break |
10 minutes |
50 minutes |
Recording from the lecture#
If you missed the class, or you want to revisit some content, download the lecture recording part 1 and part 2.