ML Parameters Optimization: GridSearch, Bayesian, Random

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ML Parameters Optimization: GridSearch, Bayesian, Random

Coursera · Beginner ·🔢 Mathematical Foundations ·3mo ago

Key Takeaways

This project teaches optimization of machine learning regression models parameters using GridSearch, Bayesian, and Random methods

Original Description

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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