Mini-project report

The mini-project is carried out in groups of 3 to 4 students.

Project overview

This document contains the instructions for the mini project on classification for the course Statistical Machine Learning, 1RT700. The problem is to classify the gender of the  main actors in Hollywood movies. The training set consists of roughly 1000 films and you will later be given a test set of roughly 300 films.  You are expected to (i) try some (or all) classification methods from the course and evaluate their performance on the problem, and (ii) make a decision which one to use and `put in production' against a test set. Your final prediction will be evaluated and also compared to the performances of the other student groups. You will document your project by writing a report, which will be reviewed anonymously by your peers. A very well implemented and documented project will earn you a `gold star' and a higher grade on the course.

Instructions

The instructions available here. The training data set is available here. The test data set is available here.

Important dates

The deadlines and other important dates for the project are as follows:

(submission deadlines are one minute before midnight, i.e., 23.59)

Group registration and submission

The group registration and the submission of the report and the contribution statement are done here in Studium.

Checklist before report submission (first report submission)

In order to pass (or possibly even achieve a gold star if your report is written such that a thorough understanding of the methods is conveyed and has a technical contribution beyond the minimum requirements), please check that ...

• You have read the final version of the report from start to end and made sure it is readable.
• The report does not contain material copied from elsewhere (all reports are checked for plagiarism using Urkund).
• The report is anonymous. That means you names or group number should not be included in the pdf nor in the file name.
• The report is written using the NeurIPS style and is not more than 7 pages long (excluding the reference list, and code appendix) a template that can be imported into overleaf is found here. 
• You have included everything listed in 4.1 in the instructions.
  

Checklist before second report submission

All items for the first submission applies, except that...

• ... in contrast to the first submission the submission should not be anonymous. That means you should add your names to the author list in the document.

In addition to the items in the first submission

• You have written a few sentences about how you have updated your report based on the peer-review. These sentences are submitted in the comment field when you submit your updated mini-project report.
• You have written the contribution statement in a separate document which is to be submitted here.
• You have made a prediction on the test data on your best model and the prediction is to be submitted here.

Questions

If you have questions, write in the discussion forum.