Скачать или смотреть 3 Popular Ways for Hyperparameter Tuning with Random Forest

In this video we will cover 3 different methods for Hyperparameter tuning with a Random Forest Classifier. These will include Grid Search, Randomized Search, and Bayesian Search. After introducing these concepts, we'll work through an example on a toy dataset in Python, and compare the results from these different methods.

The break-down of this video is as follows:

Introduction 00:00
What is Hyperparameter Tuning? 00:42
Random Forest Hyperparameters 04:43
Jupyter Notebook Setup 07:05
Grid Search Python Example 09:51
Randomized Search Python Example 12:50
Bayesian Search Python Example 14:54
Conclusions 19:13

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The notebook presented here can be found at:
https://github.com/insidelearningmach...

This video is based off of an article on my blog. You can find that blog article here: https://insidelearningmachines.com/hy...

My article describing the Random Forest algorithm can be found here: https://insidelearningmachines.com/bu...

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