Difference between revisions of "CS7646 Fall 2016"

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==Overview==
 
==Overview==
  
Please visit the main course page for an overall course introduction and policies: [[Machine_Learning_for_Trading_Course]].  The information on this page is specific to this semester.
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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==
 
==2016 Fall Schedule==
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==Assignments & Grading==
 
==Assignments & Grading==
  
* [[http://quantsoftware.gatech.edu/MC1-Project-1 MC1-Project-1: Assess portfolio]] 5%
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* [[http://quantsoftware.gatech.edu/MC1-Project-1 MC1-Project-1: Assess portfolio]] 4%
 
* [[http://quantsoftware.gatech.edu/MC1-Project-2 MC1-Project-2: Optimize a portfolio]] 5%
 
* [[http://quantsoftware.gatech.edu/MC1-Project-2 MC1-Project-2: Optimize a portfolio]] 5%
* MC3-Project-1: Implement and assess a regression learner using decision trees and random forests 15%
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* [[http://quantsoftware.gatech.edu/MC3-Project-1 MC3-Project-1: Implement and assess a regression learner using decision trees and random forests]] 15%
* MC2-Project-1: Build a market simulator 15%
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* [[http://quantsoftware.gatech.edu/MC2-Homework-1 MC2-Homework-1: Create a Machine Learning midterm question]] 2%
* MC2-Homework-1: Create two midterm questions 5%
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* [[http://quantsoftware.gatech.edu/MC3-Homework-1 MC3-Homework-1: Generate datasets that defeat learners]] 5%
* Midterm 20%
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* [[http://quantsoftware.gatech.edu/MC2-Project-1 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 10%
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* [[Midterm Study Guide]]
* MC3-Project-3: Q-learning maze navigation 10%
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* Midterm 15%
* MC3-Project-4: Q-learning trader 15%
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* [[http://quantsoftware.gatech.edu/MC3-Project-2 MC3-Project-2: Q-learning maze navigation]] 10%
* Piazza participation, up to 2% bonus for the most helpful contributors.
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* [[http://quantsoftware.gatech.edu/MC3-Project-3 MC3-Project-3: Implement your own "manual" quant strategy, then do it with decision tree classification, compare]] 15%
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* [[http://quantsoftware.gatech.edu/MC3-Project-4 MC3-Project-4: Q-learning trader]] 12% (replacement for Final Exam)
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* Class participation: 2%.
  
 
Thresholds:
 
Thresholds:
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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]]
* [[Midterm Study Guide]]
 
 
* [[http://quantsoftware.gatech.edu/MC3-Project-1 MC3-Project-1]]
 
* [[http://quantsoftware.gatech.edu/MC3-Project-1 MC3-Project-1]]
 
* [[http://quantsoftware.gatech.edu/MC3-Project-2 MC3-Project-2]]
 
* [[http://quantsoftware.gatech.edu/MC3-Project-2 MC3-Project-2]]
 
* [[http://quantsoftware.gatech.edu/MC3-Project-3 MC3-Project-3]]
 
* [[http://quantsoftware.gatech.edu/MC3-Project-3 MC3-Project-3]]

Latest revision as of 21:44, 28 November 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

  • Class participation: 2%.

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.