This repository documents my personal learning journey studying "An Introduction to Statistical Learning" (ISL) + Advance Sections from (ESL), implemented using Python.
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Chapter 1: Introduction — 05/19
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Chapter 2: Statistical Learning — 05/23
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Chapter 3: Linear Regression — 06/05
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Chapter 4: Classification — 07/08
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Chapter 5: Resampling Methods — 07/24
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Chapter 6: Linear Model Selection & Regularization — 08/26
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Chapter 7: Moving Beyond Linearity — 10/9
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Chapter 8: Tree-Based Methods
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Chapter 9: Support Vector Machines
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Chapter 10: Deep Learning
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Chapter 11: Survival Analysis & Censored Data
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Chapter 12: Unsupervised Learning
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Chapter 13: Multiple Testing
- An Introduction to Statistical Learning(Free PDF)
- Mathematics for Machine Learning (Additional Derivations)
- My Studying Journey On YT
- GitHub: amol-davkhar
- LinkedIn: Amol Davkhar
- Twitter/X: Amol Davkhar
“Consistency over perfection - one model, one bug, one step at a time.” 🔁