Intro to Hyperparameter Tuning with Python

Improve machine learning models with hyperparameter tuning.
Hyperparameters are values that can be adjusted to improve a Machine Learning model. In this course, you will learn industry standard techniques for hyperparameter tuning, including Grid Search, Random Search, Bayesian Optimization, and Genetic Algorithms.


* Understand the role of hyperparameters

* Improve model performance with tuning

* Pick the best tuning method for a model


### Notes on Prerequisites
We recommend that you complete [Intro to Regularization with Python](https://codecademy.com/learn/intro-to-regularization-with-python) before completing this course.

• Intro to Hyperparameter Tuning with Python: Learn about hyperparameter tuning methods in machine learning.
• Article: Hyperparameters in Machine Learning Models
• Lesson: Hyperparameter Tuning with `scikit-learn`
• Quiz: Hyperparameter Tuning
• Project: Classify Raisins with Hyperparameter Tuning!
• Informational: What's Next?