Day 10 - Underfitting and Overfitting & Random Forests (Intro to ML Lessons 5 & 6)
Welcome to Day 10 of Kaggle 30 Days of Machine Learning.
In this video, I will walk through Lesson 5 and Lesson 6 of the Kaggle Intro to Machine Learning course.
In Lesson 5, we will cover the concept of underfitting and overfitting as well as how to fine-tune hyperparameters (max leaf nodes in decision tree) in order to improve model performance.
In Lesson 6, we will learn about ensemble methods specifically, random forests. Random forests utilize multiple independent decision trees when making predictions, which reduces the risk of overfitting.
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Kaggle 30 Days of ML
https://www.kaggle.com/thirty-days-of-ml
Kaggle Intro to Machine Learning micro-course
https://www.kaggle.com/learn/intro-to...
My article on ensemble methods (random forest + gradient boosting)
https://towardsdatascience.com/battle...
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