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Schedule
!!! This website is archived. Please see the website of the latest edition of this course among the links listed here. !!!
Lecture Schedule
Lecture slides will be uploaded here before (sometimes, after) each class.
The slides are designed to act as an aid for my in-class lectures, not a replacement.
The slides will not be sufficient on their own.
Some details and other additional material might be given only in class.
Furthermore, the lectures themselves might often deviate significantly from the
textbooks in the order, presentation, and actual content.
Thus, attending all lectures is mandatory.
| Week | Topic | Textbook Chapters, Additional References | Slides |
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| 1 | Introduction and Administrivia | - | PDF PPTX |
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| 1-3 | Basics of Computer Organization and Operating Systems | Ch. 1, 2.1-2.3, 2.12, 4.1, and 5.1-5.5 of CompOrg Book;
Ch. 2, 4.1-4.2, 6, 7, 13, 14.1, 18.1, 21, 22,
26, 36, 37, 39, and 40.1-40.2 of Comet Book | PDF PPTX |
| 3 | Basics of Cloud Computing | - | PDF PPTX |
| 4-6 | Parallel and Scalable Data Processing | Ch. 9.4, 12.2, 14.1.1, 14.6, 22.1-22.3,
22.4.1, 22.8 of Cow Book;
Ch. 5, 6.1, 6.3, 6.4 of MLSys Book | PDF PPTX |
| 4 | Guest Lecture by Alkis Polyzotis (Google Brain) on Thursday, 01/30 | - | - |
| 4 | Review for Midterm Exam on Friday, 01/31 | - | - |
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| 5 | Midterm Exam on Thursday, 02/06 | - | - |
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| 7-8 | ML Data Preparation and Model Selection | Ch. 8.1-8.4 of MLSys Book | PDF PPTX |
| 8-9 | Dataflow Systems | Ch. 2.2 of MLSys Book | PDF PPTX Last Part Video |
| 9 | Guest Lecture by Manasi Vartak (Verta.AI) on Thursday, 03/05 | - | - |
| 10 | Deep Learning Systems | - | PDF PPTX Video |
| 10 | Optional: ML Deployment | - | PDF PPTX |
| 10 | Optional: Open Research Questions | - | PDF PPTX |
| 10 | Review for Final Exam on Thursday, 03/12 | - | - |
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| 11 | Final Exam on Tuesday, 03/17 | - | -
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Programming Assignment (PA) Schedule
It is okay to discuss about the assignment with your peers at a conceptual level.
It is also okay to post conceptual or high-level questions, logistical questions, and useful references on Piazza.
But do not share any code across teams and do not post any code on Piazza.
A team's code submission must be entirely their own.
We will use advanced program analysis tools to compare your code submissions.
If plagiarism is detected in your code, University authorities will be notified for appropriate
disciplinary action to be taken. You will also get zero for that assignment.
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