Difference between revisions of "CS7646 Fall 2016"

From Quantitative Analysis Software Courses
Jump to navigation Jump to search
Line 13: Line 13:
 
* [[http://quantsoftware.gatech.edu/MC3-Project-1 MC3-Project-1: Implement and assess a regression learner using decision trees and random forests]] 15%
 
* [[http://quantsoftware.gatech.edu/MC3-Project-1 MC3-Project-1: Implement and assess a regression learner using decision trees and random forests]] 15%
 
* [[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%)
 +
* [[Midterm Study Guide]]
 
* MC2-Project-1: Build a market simulator 15%
 
* MC2-Project-1: Build a market simulator 15%
 
* MC2-Homework-1: Create a midterm question regarding Machine Learning 2%
 
* MC2-Homework-1: Create a midterm question regarding Machine Learning 2%
Line 34: Line 35:
 
* [[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]]

Revision as of 19:25, 29 September 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.