Hyperparameter Tuning in Python
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Course overview
- Provider
- Datacamp
- Course type
- Free trial availiable
- Deadline
- Flexible
- Duration
- 4 hours
- Certificate
- Available on completion
- Course author
- Alex Scriven
Description
Learn to tune hyperparameters in Python.
Building powerful machine learning models depends heavily on the set of hyperparameters used. But with increasingly complex models with lots of options, how do you efficiently find the best settings for your particular problem? In this course you will get practical experience in using some common methodologies for automated hyperparameter tuning in Python using Scikit Learn. These include Grid Search, Random Search & advanced optimization methodologies including Bayesian & Genetic algorithms . You will use a dataset predicting credit card defaults as you build skills to dramatically increase the efficiency and effectiveness of your machine learning model building.
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