MC3-Project-3
Jump to navigation
Jump to search
Contents
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).