ML Parameters Optimization: GridSearch, Bayesian, Random
$9.99
ENROLL NOWCourse Overview
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.
Course FAQs
What are the prerequisites for 'ML Parameters Optimization: GridSearch, Bayesian, Random'?
Prerequisites for this continuing education class are set by Coursera Project Network. Most professional development online classes benefit from some prior knowledge. Please check the provider's page for specific requirements.
Will I receive a certificate for this CE class?
Yes, upon successful completion, Coursera Project Network typically offers a shareable certificate to showcase your new skills and fulfill your continuing education requirements.
How long does this online course take to complete?
Completion times for online continuing education courses vary. The provider's website will have the most accurate estimate of the time commitment needed.
