ML Parameters Optimization: GridSearch, Bayesian, Random
Completed by Oluwaseun Otunuga
July 17, 2024
1 hours (approximately)
Oluwaseun Otunuga's account is verified. Coursera certifies their successful completion of ML Parameters Optimization: GridSearch, Bayesian, Random
What you will learn
Understand the difference between hyperparameters optimization techniques such as GridSearch, Bayesian & Random Search Optimization Techniques.
Optimize ML model hyperparameters in Scikit-Learn using GridSearch, Bayesian & Random Search Optimization Techniques.
Evaluate several trained regression models performance using various Key Performance Indicators (KPIs).
Skills you will gain
- Category: Regression Analysis
- Category: Model Evaluation
- Category: Machine Learning
- Category: Model Optimization
- Category: Scikit Learn (Machine Learning Library)
- Category: Fine-tuning
- Category: Data Analysis
- Category: Applied Machine Learning
