CS246
Mining Massive Data Sets
Winter 2016
The course will discuss data mining and machine learning algorithms for analyzing very large amounts of data. The emphasis will be on Map Reduce as a tool for creating parallel algorithms that can process very large amounts of data.
Announcements:
Final Exam
Final exam for this class will be in Dinkelspiel Auditorium from 8:30AM - 11:30AM on March 16 (Wednesday). For more information about the exam, refer to post @638 on Piazza.
Other Announcements
- 1/4: The first class will be held at 9am on Tuesday, January 5, in NVIDIA Auditorium, Huang Engineering Center.
- 1/4: HW0 (Hadoop tutorial) is out, due on January 12 at 11:59pm.
- 1/5: GHW1 has been assigned on Gradiance, due on January 14 at 11:59pm.
- 1/6: Daniel Templeton (CS246H) will be holding additional office hours to help students with VM/Hadoop setup and questions on Friday (1/8) and Monday (1/11). Time: 7pm-9pm. Location: Gates B28.
- 1/7: HW1 is out, due on January 21 at 11:59pm. Find submission templates on the course handouts page.
- 1/18: Just a reminder that GHW2 has been assigned on Gradiance, due on January 21 at 11:59pm. See course info page for a complete schedule of Gradiance homeworks.
- 1/21: GHW3 has been assigned on Gradiance, due on January 28 at 11:59pm.
- 1/21: HW2 is out, due on February 04 at 11:59pm. Find submission templates on the course handouts page.
- 1/26: GHW4 has been assigned on Gradiance, due on February 4 at 11:59pm.
- 2/2: GHW5 has been assigned on Gradiance, due on February 11 at 11:59pm.
- 2/4: HW3 is out, due on February 18 at 11:59pm. Find submission templates on the course handouts page.
- 2/9: GHW6 has been assigned on Gradiance, due on February 18 at 11:59pm.
- 2/16: GHW7 has been assigned on Gradiance, due on February 25 at 11:59pm.
- 2/18: Last two Gradiance assignments will be due on the following days: GHW8 due on March 03 at 11:59pm and GHW9 due on March 10 at 11:59pm.
- 2/19: HW4 is out, due on March 03 at 11:59pm. Find submission templates on the course handouts page.
- 2/22: Final exams from 2011 and 2013 (with solutions) have been posted.
Course information:
Lectures:
Tuesday & Thursday 9AM - 10:20AM in NVIDIA Auditorium, Jen-Hsun Huang Engineering Center.
Watch video lectures on SCPD. Stanford students can see them here.
Instructor:
Jeff Ullman
Office: 425 Gates
Email: lastname @ gmail.com
Office Hours: Tuesday 10:30AM-Noon, Friday 10:30AM-Noon
Companion course CS246H:
There is a companion course
CS246H, which is completely independent from CS246 and covers Hadoop programming. It meets Tuesdays 3PM - 4:20PM, also in NVIDIA Auditorium
Office hours:
Note: Jeff Ullman will not hold office hours on 1/26, 1/29, and 2/9.
Name | Day | Hours | Location |
Jeff Ullman | Tuesday | 10:30AM-noon | 425 Gates |
Jeff Ullman | Friday | 10:30AM-noon | 425 Gates |
Caroline Suen | Monday | 1:30PM-3:30PM | 414 Gates |
Duyun Chen | Monday | 5PM-7PM | Huang Basement |
Shubham Gupta | Tuesday | 10:30AM-11:30AM | Huang Basement |
Ivaylo Bahtchevanov | Tuesday | 1PM-3PM | Huang Basement |
Jacky Wang | Tuesday | 4PM-6PM | Huang Basement |
Leon Yao | Wednesday | 11AM-1PM | Huang Basement |
Himabindu Lakkaraju | Wednesday | 2PM-4PM | 448 Gates |
Jeff Hwang | Wednesday | 6PM-8PM | Huang Basement |
Shubham Gupta | Thursday | 10:30AM-11:30AM | Huang Basement |
Tim Althoff | Thursday | 3PM-5PM | 414 Gates |
Sameep Bagadia | Friday | 3PM-5PM | Huang Basement |
You Zhou | Friday | 9AM-11AM | Huang Basement |
Nihit Desai | Friday | 1PM-3PM | Huang Basement |
Course materials:
Automated Quizzes: We will be using Gradiance. Everyone should create an account there
(passwords are at least 10 letters and digits with at least one of each) and enter the class code 62B99A55. Please use your real first and last name, with the standard capitalization, e.g., "Jeffrey Ullman" so we can match your Gradiance score report to
other class grades.
Books: Leskovec-Rajaraman-Ullman: Mining of Massive Datasets can be downloaded for free. It can be purchased from Cambridge University Press, but you are not required to do so.
MOOC: There is a Coursera MOOC that is similar to this course. You may find
it useful to view some of the videos there.
Piazza: Piazza Discussion Group for this class (access code "mmds").
Course handouts: Available here.