- Statistical Machine Learning
- Performance Tuning
- Applied Machine Learning
- Scikit Learn (Machine Learning Library)
- Machine Learning
- Bayesian Statistics
- Machine Learning Methods
- Regression Analysis
- Data Analysis
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
