10-601, Spring 2017

School of Computer Science

Carnegie Mellon University

There will be 8 problem sets during the semester in addition to the exams. Problem sets will consist of both theoretical and programming problems.

- Homework 1: Background Exercises
- Homework 2: KNN, MLE, Naive Bayes
- Homework 3: Linear Regression and Logistic Regression
- Homework 4: Regularization, Kernel, Perceptron and SVM
- Homework 5: Researching Applications of Machine Learning
- Homework 6: Unsupervised Learning
- Homework 7: (Not yet released)
- Homework 8: (Not yet released)