CS7646 Summer 2017 ATL - Revision history

Bhrolenok3: /* Office hours */

2017-06-08T17:52:54Z

Office hours

Dave: /* 2017 Summer Schedule */

2017-05-24T20:01:24Z

2017 Summer Schedule

Dave: /* Office hours */

2017-05-19T20:57:17Z

Office hours

Dave: /* Assignments & Grading */

2017-05-13T16:57:44Z

Assignments & Grading

Dave: /* Assignments */

2017-05-13T16:57:23Z

Assignments

Dave: /* Office hours */

2017-05-12T20:42:42Z

Office hours

Dave: ATL differences for Summer 2017

2017-05-12T20:42:16Z

ATL differences for Summer 2017

New page

==Overview==

This summer, the course will follow this broad outline:

# Brief introduction to Manipulating Financial Data in Python
# Introduction to Machine Learning
# Computational Investing
# Machine Learning Algorithms for Trading

==Instructor information==
[http://imtc.gatech.edu/people/c-david-byrd David Byrd]<BR>
Research Scientist, [http://imtc.gatech.edu Interactive Media Technology Center] at Georgia Tech<BR>

==2017 Summer Schedule==

Class meets MW 12:30 - 2:20 in Klaus 1456

==2017 Summer Schedule==

This schedule is tentative and subject to change due to the compressed summer timeline. I am not certain exactly how quickly we will progress through the material.

The '''first exam''' will be given in week 6 or 7 depending on our progress. I will nail it down early in the class.

The '''second exam''' will be given on the final day of regular class in week 10.

{| class="wikitable"
! Week !! Topic !! Due
|-
|1 || Course Overview, Intro to Markets, Intro to Machine Learning, Pandas Tutorial ||
|-
|2 || Visualizing Market Data, Pricing Stocks, Numpy Tutorial, Working with Time Series ||
|-
|3 || Incomplete Data, Plots, ML Lexicon/Taxonomy, Evaluating Learners ||
|-
|4 || Supervised Learning (KNN, LinReg, Decision Trees, Boosting, Bagging) ||
|-
|5 || Market History, Actors, Order Book, Order Types ||
|-
|6 || Markets, Valuation, Capitalization, Time Value of Money ||
|-
|7 || Options, Leverage ||
|-
|8 || Technical Analysis, Candlestick Chart Patterns, CAPM, Efficient Market Hypothesis ||
|-
|9 || Fund. Law of APM, Efficient Frontier, Finite Automata, Markov Decision Processes ||
|-
|10 || Value Iteration, Q-Learning ||
|}

==Assignments==

This is a project-heavy class. There will be 5 projects this semester, due roughly every two weeks. Note that there are two non-cumulative exams during the semester. The final project in the class (and the most complex) will be due during the final exam period, in lieu of a final exam.

Assignment details will be added here.

==Office hours==

David Byrd (Instructor), <B>TBD</B>
TAs TBD

← Older revision		Revision as of 17:52, 8 June 2017
Line 63:		Line 63:
	David Byrd (Instructor), <B>MW 2:20-3:30, Klaus 1456</B>. There is no class after ours in the classroom, so I will simply stay there for up to an hour every class, as long as anyone wants to talk to me!		David Byrd (Instructor), <B>MW 2:20-3:30, Klaus 1456</B>. There is no class after ours in the classroom, so I will simply stay there for up to an hour every class, as long as anyone wants to talk to me!

−	~~TAs TBD~~. ~~A poll was sent out for TA office~~ hours ~~via T-Square~~. ~~Be sure to complete it!~~	+	Brian Hrolenok, <b>ThF 4:00-5:00pm, CCB 1F Commons</b>.
		+
		+	Nitin Kodialbail, <b>Tu 3:00-5:00pm, CCB 1F Commons</b>.
		+
		+	Office hours are also posted on Piazza, which may be updated more frequently than this page:
		+	https://piazza.com/class/j2ku8wm3j6o1p9?cid=83

@@ Line 60: / Line 60: @@
 ==Office hours==
-David Byrd (Instructor), <B>TBD</B>
+David Byrd (Instructor), <B>MW 2:20-3:30, Klaus 1456</B>.  There is no class after ours in the classroom, so I will simply stay there for up to an hour every class, as long as anyone wants to talk to me!
-TAs TBD
+TAs TBD.  A poll was sent out for TA office hours via T-Square.  Be sure to complete it!

@@ Line 56: / Line 56: @@
 Assignments are available on the main course page and are the same for the on-campus and online class.
-'''Participation''': For the 3% participation credit, Piazza participation is ''not'' necessary for on campus students.  Participation will be judged based on attendance and participation at the lectures.
+'''Participation''': For the 3% participation credit, Piazza participation is ''not'' necessary for on campus students.  Participation will be judged based on attendance and attention at the lectures.
 ==Office hours==

@@ Line 32: / Line 32: @@
 |2 || Visualizing Market Data, Pricing Stocks, Numpy Tutorial, Working with Time Series ||
 |-
-|3 || Incomplete Data, Plots, ML Lexicon/Taxonomy, Evaluating Learners ||
+|3 || Incomplete Data, Plots, ML Lexicon/Taxonomy, Evaluating Learners ||MC1-P1
 |-
 |4 || Supervised Learning (KNN, LinReg, Decision Trees, Boosting, Bagging) ||
 |-
-|5 || Market History, Actors, Order Book, Order Types ||
+|5 || Market History, Actors, Order Book, Order Types ||MC3-P1 + MC3-HW1
 |-
-|6 || Markets, Valuation, Capitalization, Time Value of Money ||
+|6 || Markets, Valuation, Capitalization, Time Value of Money ||Exam 1
 |-
-|7 || Options, Leverage ||
+|7 || Options, Leverage ||MC2-P1
 |-
 |8 || Technical Analysis, Candlestick Chart Patterns,  CAPM, Efficient Market Hypothesis ||
 |-
-|9 || Fund. Law of APM, Efficient Frontier, Finite Automata, Markov Decision Processes ||
+|9 || Fund. Law of APM, Efficient Frontier, Finite Automata, Markov Decision Processes ||MC3-P2
 |-
-|10 || Value Iteration, Q-Learning ||
+|10 || Value Iteration, Q-Learning || Exam 2
 |}
 ==Assignments & Grading==

@@ Line 50: / Line 50: @@
-==Assignments==
+==Assignments & Grading==
 This is a project-heavy class.  There will be 5 projects this semester, due roughly every two weeks.  Note that there are two non-cumulative exams during the semester.  The final project in the class  (and the most complex) will be due during the final exam period, in lieu of a final exam.
-Assignment details will be added here.
+Assignments are available on the main course page and are the same for the on-campus and online class.
 ==Office hours==

← Older revision		Revision as of 20:42, 12 May 2017
Line 60:		Line 60:

	David Byrd (Instructor), <B>TBD</B>		David Byrd (Instructor), <B>TBD</B>
		+
	TAs TBD		TAs TBD