Machine Learning, Spring 2013 FINAL PROJECT **in pairs of individually** Important Dates --------------------------------- Mon 4/22: please talk to me about your topic. Wed 4/24: proposal due (should include plans for data, eval, and baseline!). Thu 4/25: optional feedback to students whose proposals need major revisions. Mon 5/13: midway presentation and feedback. Sun 5/26: final report due. Proposal Must Include At Least ------------------- 0. A clear statement of the *goal* of the project. What's the problem? 1. The linguistics relevance of this project, as well as the computational perspective. Why is the problem interesting, relevant, and reasonably hard? 2. Description of the existing methods for this problem? What has been done before and how is it solved today? 3. Description of the *new methods* you propose to use. 4. Concrete description of the *data* that you will use, how/where to get it, and what (pre-)processing is needed to make it useable. 5. Description of the *evaluation* method that you will use. How do you know if you're successful? 6. Description of a *baseline* method, i.e. something that you can implement in *two hours* to attack the problem. See Also: Heilmeier Catchism for proposal writing. TOPIC -------------------------------------------- 1. A natural topic could be based on homework assignments: either combining two homeworks, or improving upon one homework (see examples below) or (preferably) part of a larger research project you are working on, and/or (ideally) something fun and exciting! 2. It is preferred that your project has some connections to the topics we covered: perceptron, kernels, SVM, structured prediction, and topics we're going to cover: unsupervised learning, k-means clustering, EM, mixture of gaussians, dimensionality reduction (PCA/ICA). 3. Note that that the instructor makes the final decision to approve each topic and expect and will reward *originality*, depth, and relevance. Please talk to me about your topic before writing the proposal.