Difference between revisions of "CS7646 Summer 2017"
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==Assignments & Grading== | ==Assignments & Grading== | ||
| − | '''Projects ( | + | '''Projects (62%)''' |
* [[http://quantsoftware.gatech.edu/MC1-Project-1 MC1-Project-1: Assess portfolio]] 5% (easy) | * [[http://quantsoftware.gatech.edu/MC1-Project-1 MC1-Project-1: Assess portfolio]] 5% (easy) | ||
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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% (hard) | * [[http://quantsoftware.gatech.edu/MC3-Project-1 MC3-Project-1: Implement and assess a regression learner using decision trees and random forests]] 15% (hard) | ||
| + | * [[http://quantsoftware.gatech.edu/MC2-Project-1 MC2-Project-1: Build a market simulator]] 15% (moderate) | ||
* [[http://quantsoftware.gatech.edu/MC3-Project-2 MC3-Project-2: Q-learning maze navigation]] 10% (easy) | * [[http://quantsoftware.gatech.edu/MC3-Project-2 MC3-Project-2: Q-learning maze navigation]] 10% (easy) | ||
| − | * [[http://quantsoftware.gatech.edu/MC3-Project-3 MC3-Project-3: Implement a "manual" quant strategy, then do it with decision tree classification]] | + | * Trading Strategy Learner 17% (very hard) |
| − | * [[http://quantsoftware.gatech.edu/MC3-Project-4 MC3-Project-4: Q-learning trader]] | + | ** mixture of [[http://quantsoftware.gatech.edu/MC3-Project-3 MC3-Project-3: Implement a "manual" quant strategy, then do it with decision tree classification]] |
| − | + | ** and [[http://quantsoftware.gatech.edu/MC3-Project-4 MC3-Project-4: Q-learning trader]] | |
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'''Homework (5%):''' | '''Homework (5%):''' | ||
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* [[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% | ||
| − | '''Exams ( | + | '''Exams (30%)''' |
* [[Midterm Study Guide]] | * [[Midterm Study Guide]] | ||
* [[Final Study Guide]] | * [[Final Study Guide]] | ||
| − | * Midterm | + | * Midterm 15% |
| − | * Final | + | * Final 15% |
'''Class participation (3%)''' | '''Class participation (3%)''' | ||
Revision as of 12:54, 13 May 2017
Contents
Overview
You are on the page for information specific to the Summer 2017 session of this course. Go here (Machine_Learning_for_Trading_Course) for overall course policies.
Important Note
This is currently a duplicate of Spring 2017, a work in progress for Summer 2017.
Specific On-Campus Information
- Any on-campus deviations (related to office hours, exams, lecture times/topics/notes) can be found here: CS7646_Summer_2017_ATL
2017 Spring Schedule
- [[1]]
Assignments & Grading
Projects (62%)
- [MC1-Project-1: Assess portfolio] 5% (easy)
- [MC3-Project-1: Implement and assess a regression learner using decision trees and random forests] 15% (hard)
- [MC2-Project-1: Build a market simulator] 15% (moderate)
- [MC3-Project-2: Q-learning maze navigation] 10% (easy)
- Trading Strategy Learner 17% (very hard)
Homework (5%):
Exams (30%)
- Midterm Study Guide
- Final Study Guide
- Midterm 15%
- Final 15%
Class participation (3%)
- Class participation is determined by activity on piazza.
Thresholds
- A: 90% and above
- B: 80% and above
- C: 70% and above
- D: 60% and above
- F: below 60%
These are hard boundaries (we round down).
