Back to ML Parameters Optimization: GridSearch, Bayesian, Random
Learner Reviews & Feedback for ML Parameters Optimization: GridSearch, Bayesian, Random by Coursera Project Network
About the Course
Hello everyone and welcome to this new hands-on project on Machine Learning hyperparameters optimization. In this project, we will optimize machine learning regression models parameters using several techniques such as grid search, random search and Bayesian optimization. Hyperparameter optimization is a key step in developing machine learning models and it works by fine tuning ML models so they can optimally perform on a given dataset.
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1 - 1 of 1 Reviews for ML Parameters Optimization: GridSearch, Bayesian, Random
By Ariel F
•Sep 30, 2022
Another great course!