github-starred/cs249r_book
2
0
Fork 0
mirror of https://github.com/harvard-edge/cs249r_book.git synced 2026-07-15 21:28:33 -05:00
Code Issues 270 Packages Projects Releases 26 Wiki Activity

[PR #237] [MERGED] Improved grammar and readability of the introduction section #14771

New Issue
Closed
opened 2026-05-20 13:24:18 -05:00 by GiteaMirror · 0 comments
GiteaMirror commented 2026-05-20 13:24:18 -05:00
Owner
Copy Link

📋 Pull Request Information

Original PR: https://github.com/harvard-edge/cs249r_book/pull/237
Author: @Sara-Khosravi
Created: 5/31/2024
Status: ✅ Merged
Merged: 6/1/2024
Merged by: @profvjreddi

Base: dev ← Head: improve-introduction-section

📝 Commits (2)

  • c04fb26 Improved grammar and readability of the introduction section
  • bfee051 Put back the reference / URL links

📊 Changes

1 file changed (+4 additions, -4 deletions)

View changed files

📝 contents/introduction/introduction.qmd (+4 -4)

📄 Description

Summary
This pull request addresses several typos and grammatical issues in the introduction of the TinyML book. The changes aim to improve the readability and clarity of the text.

Changes Made

  1. Corrected spelling mistakes ("The key to this ubiquitous intelligence lies in developing and deploying machine learning systems at the edge of our networks." to "The crucial aspect of this ubiquitous intelligence is the development and implementation of machine learning systems at the edge of our networks.").
  2. Improved sentence structure for better readability.
  3. Fixed punctuation errors.
  4. Replaced informal language with more formal equivalents.

Specific Edits
#sec-introduction-1:
• Changed "a crisp" to "a crisp,"
#sec-introduction-2:
• Changed "computing would so be seamlessly integrated" to "computing would be seamlessly integrated" #sec-introduction-3:
• Changed "The key to this ubiquitous intelligence lies in developing and deploying machine learning systems at the edge of our networks." to "The crucial element of this ubiquitous intelligence is developing and deploying machine learning systems at the edge of our networks." #sec-introduction-4:
• Improved sentence:
Original: “Machine learning, a subset of artificial intelligence, enables computers to learn from and make decisions based on data rather than following explicitly programmed instructions. When deployed at the edge—closer to where data is generated, and actions are taken—machine learning systems can process information in real-time, responding to environmental changes and user inputs with minimal latency. This capability is critical for applications where timing is crucial, such as autonomous vehicles, real-time language translation, and smart healthcare devices.”
Revised: “Machine learning, a subset of artificial intelligence, enables computers to learn from and make decisions based on data rather than following explicitly programmed instructions. When deployed at the edge, closer to data generation and action, these systems can process information in real time with minimal latency. This is critical for TinyML applications, where fast response is crucial, such as autonomous vehicles, real-time translation, and smart healthcare devices.”
Suggestion: Consider strengthening the connection to TinyML by emphasizing its applications throughout the introduction.

Reviewer's Notes
Please review the changes and let me know if further modifications are needed. Your feedback is very important to me for the other chapters. Thank you very much!

Before submitting your Pull Request, please ensure that you have carefully reviewed and completed all items on this checklist.

  1. Content

    • The chapter content is complete and covers the topic in detail.
    • All technical terms are well-defined and explained.
    • Any code snippets or algorithms are well-documented and tested.
    • The chapter follows a logical flow and structure.

  2. References & Citations

    • All references are correctly listed at the end of the chapter.
    • In-text citations are used appropriately and match the references.
    • All figures, tables, and images have proper sources and are cited correctly.

  3. Quarto Website Rendering

    • The chapter has been locally built and tested using Quarto.
    • All images, figures, and tables render properly without any glitches.
    • All images have a source or they are properly linked to external sites.
    • Any interactive elements or widgets work as intended.
    • The chapter's formatting is consistent with the rest of the book.

  4. Grammar & Style

    • The chapter has been proofread for grammar and spelling errors.
    • The writing style is consistent with the rest of the book.
    • Any jargon is clearly explained or avoided where possible.

  5. Collaboration

    • All group members have reviewed and approved the chapter.
    • Any feedback from previous reviews or discussions has been addressed.

  6. Miscellaneous

    • All external links (if any) are working and lead to the intended destinations.
    • If datasets or external resources are used, they are properly credited and linked.
    • Any necessary permissions for reused content have been obtained.

  7. Final Steps

    • The chapter is pushed to the correct branch on the repository.
    • The Pull Request is made with a clear title and description.
    • The Pull Request includes any necessary labels or tags.
    • The Pull Request mentions any stakeholders or reviewers who should take a look.

🔄 This issue represents a GitHub Pull Request. It cannot be merged through Gitea due to API limitations.

## 📋 Pull Request Information **Original PR:** https://github.com/harvard-edge/cs249r_book/pull/237 **Author:** [@Sara-Khosravi](https://github.com/Sara-Khosravi) **Created:** 5/31/2024 **Status:** ✅ Merged **Merged:** 6/1/2024 **Merged by:** [@profvjreddi](https://github.com/profvjreddi) **Base:** `dev` ← **Head:** `improve-introduction-section` --- ### 📝 Commits (2) - [`c04fb26`](https://github.com/harvard-edge/cs249r_book/commit/c04fb266dc471a73ffa3a5ccb5dc241ca71386c5) Improved grammar and readability of the introduction section - [`bfee051`](https://github.com/harvard-edge/cs249r_book/commit/bfee051b91016f3ca17a93f0158d48a9ab97d87f) Put back the reference / URL links ### 📊 Changes **1 file changed** (+4 additions, -4 deletions) <details> <summary>View changed files</summary> 📝 `contents/introduction/introduction.qmd` (+4 -4) </details> ### 📄 Description Summary This pull request addresses several typos and grammatical issues in the introduction of the TinyML book. The changes aim to improve the readability and clarity of the text. Changes Made 1. Corrected spelling mistakes ("The key to this ubiquitous intelligence lies in developing and deploying machine learning systems at the edge of our networks." to "The crucial aspect of this ubiquitous intelligence is the development and implementation of machine learning systems at the edge of our networks."). 2. Improved sentence structure for better readability. 3. Fixed punctuation errors. 4. Replaced informal language with more formal equivalents. Specific Edits #sec-introduction-1: • Changed "a crisp" to "a crisp," #sec-introduction-2: • Changed "computing would so be seamlessly integrated" to "computing would be seamlessly integrated" #sec-introduction-3: • Changed "The key to this ubiquitous intelligence lies in developing and deploying machine learning systems at the edge of our networks." to "The crucial element of this ubiquitous intelligence is developing and deploying machine learning systems at the edge of our networks." #sec-introduction-4: • Improved sentence: Original: “Machine learning, a subset of artificial intelligence, enables computers to learn from and make decisions based on data rather than following explicitly programmed instructions. When deployed at the edge—closer to where data is generated, and actions are taken—machine learning systems can process information in real-time, responding to environmental changes and user inputs with minimal latency. This capability is critical for applications where timing is crucial, such as autonomous vehicles, real-time language translation, and smart healthcare devices.” Revised: “Machine learning, a subset of artificial intelligence, enables computers to learn from and make decisions based on data rather than following explicitly programmed instructions. When deployed at the edge, closer to data generation and action, these systems can process information in real time with minimal latency. This is critical for TinyML applications, where fast response is crucial, such as autonomous vehicles, real-time translation, and smart healthcare devices.” Suggestion: Consider strengthening the connection to TinyML by emphasizing its applications throughout the introduction. Reviewer's Notes Please review the changes and let me know if further modifications are needed. Your feedback is very important to me for the other chapters. Thank you very much! Before submitting your Pull Request, please ensure that you have carefully reviewed and completed all items on this checklist. 1. **Content** - [ ] The chapter content is complete and covers the topic in detail. - [ ] All technical terms are well-defined and explained. - [ ] Any code snippets or algorithms are well-documented and tested. - [ ] The chapter follows a logical flow and structure. 2. **References & Citations** - [ ] All references are correctly listed at the end of the chapter. - [ ] In-text citations are used appropriately and match the references. - [ ] All figures, tables, and images have proper sources and are cited correctly. 3. **Quarto Website Rendering** - [ ] The chapter has been locally built and tested using Quarto. - [ ] All images, figures, and tables render properly without any glitches. - [ ] All images have a source or they are properly linked to external sites. - [ ] Any interactive elements or widgets work as intended. - [ ] The chapter's formatting is consistent with the rest of the book. 4. **Grammar & Style** - [ ] The chapter has been proofread for grammar and spelling errors. - [ ] The writing style is consistent with the rest of the book. - [ ] Any jargon is clearly explained or avoided where possible. 5. **Collaboration** - [ ] All group members have reviewed and approved the chapter. - [ ] Any feedback from previous reviews or discussions has been addressed. 6. **Miscellaneous** - [ ] All external links (if any) are working and lead to the intended destinations. - [ ] If datasets or external resources are used, they are properly credited and linked. - [ ] Any necessary permissions for reused content have been obtained. 7. **Final Steps** - [ ] The chapter is pushed to the correct branch on the repository. - [ ] The Pull Request is made with a clear title and description. - [ ] The Pull Request includes any necessary labels or tags. - [ ] The Pull Request mentions any stakeholders or reviewers who should take a look. --- <sub>🔄 This issue represents a GitHub Pull Request. It cannot be merged through Gitea due to API limitations.</sub>
GiteaMirror added the pull-request label 2026-05-20 13:24:18 -05:00
Sign in to join this conversation.
No Branch/Tag Specified
Branches Tags
Labels
Clear labels
area: book
area: collabs
area: kits
area: labs
area: socratiq
area: staffml
area: tinytorch
area: tools
area: website
bug
dependencies
format: epub
format: pdf
javascript
link-health
link-rot
priority-high
pull-request
Mirrored from GitHub Pull Request
 staffml
type: bug
type: citation
type: code
type: errata
type: improvement
type: new
type: question
vault-sli
No Label pull-request
Milestone
No items
No Milestone
Projects
Clear projects
No project
Assignees
Clear assignees
GiteaMirror ninjasurge
No Assignees
1 Participants
Notifications
Due Date
No due date set.
Dependencies

No dependencies set.

Reference: github-starred/cs249r_book#14771
Delete Branch "%!s()"

Deleting a branch is permanent. Although the deleted branch may continue to exist for a short time before it actually gets removed, it CANNOT be undone in most cases. Continue?