fin-ecmt

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:

1. Introduction, statistical learning and linear regression model (Chapters 1-3).

2. Classification (Chapter 4).

3. Resampling methods (Chapter 5).

4. Linear model selection and regularization (Chapter 6).

5. Moving beyond linearity (Chapter 7).

6. Tree-based methods (Chapter 8).

7. Support Vector Machines (Chapter 9).

8. Unsupervised Learning (Chapter 10).

9. The Neural Network Method (Chapter 11 of the lecture note, if time permits)

10. 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