Difference between revisions of "CS7646 Fall 2016"

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* [[http://quantsoftware.gatech.edu/MC2-Homework-1 MC2-Homework-1: Create a Machine Learning midterm question]] 2%
 
* [[http://quantsoftware.gatech.edu/MC2-Homework-1 MC2-Homework-1: Create a Machine Learning midterm question]] 2%
 
* [[http://quantsoftware.gatech.edu/MC3-Homework-1 MC3-Homework-1: Generate datasets that defeat learners]] 5%
 
* [[http://quantsoftware.gatech.edu/MC3-Homework-1 MC3-Homework-1: Generate datasets that defeat learners]] 5%
 +
* [[http://quantsoftware.gatech.edu/MC2-Project-1 MC2-Project-1: Build a market simulator]] 15%
 
* [[Midterm Study Guide]]
 
* [[Midterm Study Guide]]
 
* Midterm 15%
 
* Midterm 15%
* MC2-Project-1: Build a market simulator 15%
 
 
* MC3-Project-2: Implement your own "manual" quant strategy, then do it with decision tree classification, compare 12%
 
* MC3-Project-2: Implement your own "manual" quant strategy, then do it with decision tree classification, compare 12%
 
* MC3-Project-3: Q-learning maze navigation 10%
 
* MC3-Project-3: Q-learning maze navigation 10%
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The projects linked to below are from previous semesters.  We keep them here so you can peek ahead, but please keep in mind that they will be revised.
 
The projects linked to below are from previous semesters.  We keep them here so you can peek ahead, but please keep in mind that they will be revised.
  
* [[http://quantsoftware.gatech.edu/MC2-Project-1 MC2-Project-1: Build a market simulator]]
 
 
* [[http://quantsoftware.gatech.edu/MC2-Project-2 MC2-Project-2: Implement bollinger bands, and create a simple trading strategy]]
 
* [[http://quantsoftware.gatech.edu/MC2-Project-2 MC2-Project-2: Implement bollinger bands, and create a simple trading strategy]]
 
* [[http://quantsoftware.gatech.edu/MC2-Homework-1 MC3-Homework-1: Create a Finance midterm question]]
 
* [[http://quantsoftware.gatech.edu/MC2-Homework-1 MC3-Homework-1: Create a Finance midterm question]]

Revision as of 12:32, 10 October 2016

Overview

You are on the page for information specific to the Fall 2016 session of this course. Go here (Machine_Learning_for_Trading_Course) for overall course policies.

2016 Fall Schedule

Assignments & Grading

Thresholds:

  • A: 90% and above
  • B: 80% and above
  • C: 70% and above
  • D: 60% and above
  • F: below 60%

The projects linked to below are from previous semesters. We keep them here so you can peek ahead, but please keep in mind that they will be revised.