[GH-ISSUE #810] Inspir. from Prev Textbooks - Add Exercises #5549

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opened 2026-04-21 21:29:53 -05:00 by GiteaMirror · 2 comments
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Originally created by @huskydj1 on GitHub (Apr 14, 2025).
Original GitHub issue: https://github.com/harvard-edge/cs249r_book/issues/810

Adding more exercises might help tie ideas together and make throughlines more visible.

Pseudocode

For instance, this section might benefit from an exercise about pseudocode and how a process like this would be implemented in practice (for instance, prompting the reader to write pseudocode like from the original paper, shown below).

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Tying back Concepts

Some ideas feel very high-level, and it could be helpful to draw them back to fundamentals explained earlier. For instance, how do the different memory management strategies affect the total memory equation?

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From Stanford's course, drawing back to real-world examples

This exercise draws ml system requirements to twitter's trending hashtags. Helps understand scope, iteration of ideas, etc.

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Originally created by @huskydj1 on GitHub (Apr 14, 2025). Original GitHub issue: https://github.com/harvard-edge/cs249r_book/issues/810 Adding more exercises might help tie ideas together and make throughlines more visible. ### Pseudocode For instance, this section might benefit from an exercise about pseudocode and how a process like this would be implemented in practice (for instance, prompting the reader to write pseudocode like from the original paper, shown below). ![Image](https://github.com/user-attachments/assets/ee1edda3-4e43-403c-9e80-b41237a58dc4) ![Image](https://github.com/user-attachments/assets/1b4b6cae-451d-471b-8ecf-4434bab28601) ### Tying back Concepts Some ideas feel very high-level, and it could be helpful to draw them back to fundamentals explained earlier. For instance, how do the different memory management strategies affect the total memory equation? ![Image](https://github.com/user-attachments/assets/d9b7b284-01c5-459d-aa23-5a19624f2d1e) ### From Stanford's course, drawing back to real-world examples This exercise draws ml system requirements to twitter's trending hashtags. Helps understand scope, iteration of ideas, etc. ![Image](https://github.com/user-attachments/assets/c44270b4-c896-4926-bfbe-d3fe7baeefae)
GiteaMirror added the area: tools label 2026-04-21 21:29:53 -05:00
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@profvjreddi commented on GitHub (Apr 14, 2025):

Hi @huskydj1 — thank you so much for the candid feedback!

I really appreciate it when folks take the time to share thoughtful suggestions and ideas for improvement. The book is very much a work in progress, and I take all feedback seriously -- so it genuinely helps shape and refine things as I go.

Just a quick heads-up: please don’t read the Federated Learning chapter too closely right now. I know it’s in there, but it definitely needs a full rewrite. I’m already working on a major revision offline and plan to push an update soon — hopefully by the end of the month.

And please keep the candid feedback coming — I really value it! 🙏 My process is usually iterative: I write a first version, get feedback, then revisit sections in cycles of improvement. Messages like yours are exactly what help move things forward.

By the way, if you come across anything you’d like to submit a PR for, feel free as this is a community resource, and all contributors are publicly acknowledged here: contributors.

<!-- gh-comment-id:2803268903 --> @profvjreddi commented on GitHub (Apr 14, 2025): Hi @huskydj1 — thank you so much for the candid feedback! I really appreciate it when folks take the time to share thoughtful suggestions and ideas for improvement. The book is very much a work in progress, and I take all feedback seriously -- so it genuinely helps shape and refine things as I go. Just a quick heads-up: please don’t read the Federated Learning chapter too closely right now. I know it’s in there, but it definitely needs a full rewrite. I’m already working on a major revision offline and plan to push an update soon — hopefully by the end of the month. And please keep the candid feedback coming — I really value it! 🙏 My process is usually iterative: I write a first version, get feedback, then revisit sections in cycles of improvement. Messages like yours are exactly what help move things forward. By the way, if you come across anything you’d like to submit a PR for, feel free as this is a community resource, and all contributors are publicly acknowledged here: [contributors](https://mlsysbook.ai/contents/frontmatter/acknowledgements/acknowledgements.html#contributors).
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@profvjreddi commented on GitHub (Aug 23, 2025):

Resolved - Exercises added to chapters

<!-- gh-comment-id:3217126043 --> @profvjreddi commented on GitHub (Aug 23, 2025): Resolved - Exercises added to chapters
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Reference: github-starred/cs249r_book#5549