Introduction to Machine Learning
Project Report: You should write a report that includes the sections listed below. Your report should follow the IEEE transactions format (single spaced, double column). Focus your report on your training and testing strategies for the contest and any unique implementations.
Templates for the IEEE transactions format can be found here: http://www.ieee.org/publications standards/publications/authors/author templates.html
The maximum number of pages for the report is 4. If there are any pages beyond page 4, they will discarded and not read or graded. It should be written with correct English grammar and spelling. Be precise - use pseudo-code or equations to be precise.
Abstract A summary description of the contents of the report and your findings
Introduction Overview of your experiment and a literature review. For the literature review, include any references to any relevant papers for your experiment. So, whatever you decide to do, search the ACM and IEEE (or other) literature for relevant papers to read and refer to. Implementation Describe and outline any specific implementation details for your project. A reader should be able to recreate your implementation and experiments from your project report. How will you identify characters that were not in the training data?
Experiments Carefully describe your experiments with the training dataset and any other small toy data sets you constructed. Include a description of what the goal each individual experiment is and what your findings are. This is the bulk of what you will be graded on - if your experimental design is not sound or your experiments do not make sense, you will lose points. Conclusions Describe any conclusions or things you learned from the project. Your conclusions must follow from what you did. Do not copy something out of a paper or say something that has no experimental support in the Experiments section.
References Listing of all references in IEEE bibliography format.
