Build Decision Trees from Scratch

Grow classification and regression trees by hand.

Build decision trees from an empty file: Gini impurity, best-split search, greedy recursion, pruning, and sum-of-squared-residuals for regression. Every formula is traced by hand on a toy dataset before it becomes working Python.

beginnermldecision-treesfrom-scratch

23 capsules108 figures~5 hoursby Dr. Raj Dandekar

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00Foundations4 capsules

Foundations — 4 chapters.

01Why Decision Trees?intuitionfree15 min 02The Anatomy of a Decision Treeconcept🔒13 min 03Classification vs Regression Treesconcept🔒14 min 04The Toy Dataset We Will Split by Handconcept🔒13 min

01Classification Trees9 capsules

Classification Trees — 9 chapters.

05Starting to Build a Classification Treeconcept🔒13 min 06What is Gini Impurity?math🔒11 min 07Gini Impurity: A Worked Examplemath🔒14 min 08Gini Impurity for Numerical Featuresmath🔒13 min 09Choosing the Best Splitintuition🔒13 min 10Recursion and Stopping Rulesconcept🔒15 min 11Finishing the Classification Treeconcept🔒14 min 12Pruning to Fight Overfittingdeep-dive🔒14 min 13Code an Entire Classification Tree in Pythoncode🔒15 min

02Regression Trees7 capsules

Regression Trees — 7 chapters.

14What are Regression Trees?concept🔒15 min 15Variance and SSR as the Split Criterionmath🔒12 min 16Building the First Regression Splitintuition🔒14 min 17Finishing the Regression Treeconcept🔒17 min 18Regression Trees with Multiple Featuresdeep-dive🔒15 min 19Code an Entire Regression Tree in Pythoncode🔒14 min 20Capstone: Fit and Read a Regression Treeproject🔒12 min

03Wrap-Up and Interview Prep3 capsules

Wrap-Up and Interview Prep — 3 chapters.

21Recap: Two Trees, One Algorithmintuition🔒14 min 22Interview Prep: Decision Treesconcept🔒12 min 23From One Tree to Forests and Boostingdeep-dive🔒13 min

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