This repository documents my personal learning journey studying "An Introduction to Statistical Learning" (ISL), 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- 06/30
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Chapter 5: Resampling Methods
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Chapter 6: Linear Model Selection & Regularization
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Chapter 7: Moving Beyond Linearity
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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