⬇️ Get the files and follow along: https://bit.ly/3X6IYmm
The mighty random forest is a Production-quality machine learning algorithm.
The good news is that this machine learning algorithm is as easy to understand as it is powerful.
This crash course will prove it to you.
You will also learn how to use the scikit-learn library in Python to train and evaluate random forest classifier models.
☕ If you found this content useful and would like to support the channel, you can buy me a coffee: https://www.buymeacoffee.com/DaveOnData
--------------------------------------------------------------------------------------------
Book links
--------------------------------------------------------------------------------------------
Intro to Statistical Learning:
https://www.statlearning.com/
CART book:
https://www.amazon.com/Classification-Regression-Wadsworth-Statistics-Probability/dp/0412048418/
Data Mining textbook:
https://www.amazon.com/Introduction-Mining-Whats-Computer-Science/dp/0133128903/
--------------------------------------------------------------------------------------------
Save 20% off my machine learning online courses
--------------------------------------------------------------------------------------------
Use coupon YOUTUBE.
Learn decision trees and the mighty random forest:
https://bit.ly/TDWIIntroToML
Cluster Analysis with Python online course:
https://bit.ly/ClusterAnalysisWithPythonCourse
--------------------------------------------------------------------------------------------
Video Chapters
--------------------------------------------------------------------------------------------
00:00 Intro
01:09 Why Decision Trees are a Problem
06:59 The Wisdom of the Crowd
09:04 Manufacturing Independence
10:22 Bagging
13:48 Out-of-Bag (OOB) Data
15:55 Feature Randomization
20:39 The Dataset
21:43 Preparing Features & Labels
27:04 Training a Random Forest
32:28 Get OOB Predictions
36:06 Visualize OOB Predictions
38:22 Continue Your Learning
#machinelearning #randomforest #randomforests