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In this video I go through hyperparameter fine tuning starting from not knowing what they are, all the way up to using advanced frameworks like Optuna in python. Hyperparameter fine tuning is essential for any aspiring data scientist or machine learning engineer!
📖CHAPTERS
00:00 - Intro
02:00 - Demo setup
08:22 - What even are hyperparameters?
15:12 - Manually tuning hyperparameters
17:58 - Searching parameter combinations
42:48 - Using Optuna for tuning
54:18 - Visualisation with Optuna
58:10 - Storing results in Optuna
1:02:45 - Creating multiple Optuna studies
1:06:19 - Bonus: experimental workflow with Optuna
1:17:28 - Conclusion and Thanks!
🔗LINKS
- Github repo: https://github.com/trentpark8800/hyperparameter-tuning-tutorial
- Scikit-learn article on hyperparameters: https://scikit-learn.org/stable/modules/grid_search.html#grid-search
- Optuna: https://optuna.org/#code_examples
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