MC3-Project-3

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Revision as of 17:53, 25 November 2015 by Tucker (talk | contribs) (→‎Rubric)
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Draft

Updates / FAQs

Overview

In this project you will implement and assess Q-Learning.

Template and Data

You will use data in the ML4T/data directory. In particular files named ML4T-399.csv, and IBM.csv.

Contents of Report

Hints & resources

What to turn in

Turn your project in via t-square.

  • Your report as report.pdf
  • Your code as code.py

Extra credit up to 3%

Rubric

Required, Allowed & Prohibited

Required:

  • Your project must be coded in Python 2.7.x.
  • Your code must run on one of the university-provided computers (e.g. buffet02.cc.gatech.edu), or on one of the provided virtual images.
  • Your code must run in less than 30 seconds on one of the university-provided computers.

Allowed:

  • You can develop your code on your personal machine, but it must also run successfully on one of the university provided machines or virtual images.
  • Your code may use standard Python libraries.
  • You may use the NumPy, SciPy and Pandas libraries. Be sure you are using the correct versions.
  • You may reuse sections of code (up to 5 lines) that you collected from other students or the internet.
  • Code provided by the instructor, or allowed by the instructor to be shared.

Prohibited:

  • Any libraries not listed in the "allowed" section above.
  • Any code you did not write yourself (except for the 5 line rule in the "allowed" section).
  • Any Classes (other than Random) that create their own instance variables for later use (e.g., learners like kdtree).
  • Print statements (they significantly slow down auto grading).