CS4646 Spring 2018
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Overview
You are on the page for information specific to the Spring 2018 session of CS 4646. Go here (Undergrad_ML4T) for overall course policies.
Schedule & Forum
- Forum: https://piazza.com/class/jby8m47v3v52oc (just search for CS 4646 if this doesn't work)
- Project Deadlines: All projects are due Sunday night at 11:55 PM Eastern US Time. Projects are due at the end of the week in which they are listed. For example, Project 1 (assess a portfolio) is listed as due in Week 3, meaning Sunday 1/28 -- the Sunday after Week 3.
- Late Projects: As stated in class, projects will be accepted up to 24 hours late without any excuse required. Projects one second to 24 hours late will receive a -10 penalty. After 24 hours, late projects will not be accepted for any credit at all unless arrangements were made with the instructor prior to the project deadline.
- Schedule: Subject to Change if necessary. I will give you as much notice as possible.
| Week | Date (Tues) | Weekly Topics | Due |
|---|---|---|---|
| 1 | 1/9 | Course Overview, Python/Pandas Tutorial | |
| 2 | 1/16 | Numpy Tutorial, Visualizing Market Data, Working with Time Series, Incomplete Data | |
| 3 | 1/23 | ML Lexicon/Taxonomy, Evaluating Learners | Project 1 |
| 4 | 1/30 | Supervised Learning (KNN, LinReg, Decision Trees) | |
| 5 | 2/6 | Ensembles (Bagging, Boosting), Market History, Actors | Project 2 |
| 6 | 2/13 | Order Types, Order Book, Leverage | |
| 7 | 2/20 | Valuation, Technical Analysis, Candlestick Chart Patterns | Project 3 |
| 8 | 2/27 | Time Value of Money, CAPM, Efficient Market Hypothesis | |
| 9 | 3/6 | Fund. Law of APM, Efficient Frontier, Review | Exam 1 |
| 10 | 3/13 | Finite Automata, MDP, Value/Policy Iteration, Drop Day (3/14) | Project 4 |
| 11 | 3/20 | SPRING BREAK | |
| 12 | 3/27 | Q-Learning | |
| 13 | 4/3 | Q-Learning, Misc ML Topics or Catch-up | Project 5 |
| 14 | 4/10 | Options, Time Series Q-Learning | |
| 15 | 4/17 | Review, Exam 2, Last regular day of class | Exam 2 |
| 16 | 4/24 | Final Instruction Days (Tuesday), Help Session on Final Project | Project 6 |
| 17 | 5/1 | Finals week, NO FINAL EXAM |
Assignments
Projects (60%)
- [assess_portfolio] 5% (easy)
- Regression / Ensemble Learners 10% (challenging)
- Market Simulator 10% (moderate)
- Manual Strategy 10% (moderate)
- Q-Learning Robot 10% (moderate)
- Strategy Learner 15% (very challenging)
Exams (40%)
- Exam 1: 20%
- Exam 2: 20%
Exam Study Guides
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).
