學生對 Coursera Project Network 提供的 ML Parameters Optimization: GridSearch, Bayesian, Random 的評價和反饋
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....
1 - ML Parameters Optimization: GridSearch, Bayesian, Random 的 1 個評論（共 1 個）