Problem Sets and Final Exam for Texas A&M ECMT 670: Machine Learning in Econometrics.
Textbook used: An Introduction to Statistical Learning: with application in R, (2nd ed.) by Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani.
Topics covered include:
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Introduction, statistical learning and linear regression model (Chapters 1-3).
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Classification (Chapter 4).
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Resampling methods (Chapter 5).
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Linear model selection and regularization (Chapter 6).
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Moving beyond linearity (Chapter 7).
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Tree-based methods (Chapter 8).
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Support Vector Machines (Chapter 9).
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Unsupervised Learning (Chapter 10).
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The Neural Network Method (Chapter 11 of the lecture note, if time permits)
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Nonparametric Estimation Methods (Chapter 12 of the lecture note, if time permits)
Nonparametric Estimation: Nonparametric Estimation.pdf
Problem Sets: Problem Sets.pdf
Final Exam: Final-Exam.pdf Submission: Schnabel_Exam.pdf