Machine Learning With Random Forests And Decision Trees
A Visual Guide For Beginners
by:
Scott Hartshorn
Summary:
The book provides an introductory explanation of machine learning concepts, focusing on the use of random forests and decision trees. It employs visual aids and simple language to help beginners understand the algorithms and their applications in data analysis and prediction.
Key points:
1. Decision Trees: The book explains decision trees, a model used for classification and regression. They create a tree-like decision model based on data features. Adjusting the tree's depth can increase complexity but may lead to overfitting.
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