michiganrobotics/rob101 排名第 10,098，有 1,524 个星标。
同类别比较
michiganrobotics/rob101 排名第 10,098，此处有 8 个同类条目；mikeroyal/Photogrammetry-Guide 排名第 10,083。
同类别比较| 名称 | 排名 | 指标 |
|---|
| devnag/pytorch-generative-adversarial-networks | 10,041 | - 语言:
- Python
- 星标数:
- 1,545
- 分叉数:
- 439
- 简介:
- A very simple generative adversarial network (GAN) in PyTorch
|
|---|
| scorpionhiccup/StockPricePrediction | 10,056 | - 语言:
- Jupyter Notebook
- 星标数:
- 1,539
- 分叉数:
- 436
- 简介:
- Stock Price Prediction using Machine Learning Techniques
|
|---|
| easychen/openai-gpt-dev-notes-for-cn-developer | 10,059 | - 语言:
- Shell
- 星标数:
- 1,538
- 分叉数:
- 104
- 简介:
- 如何快速开发一个OpenAI/GPT应用：国内开发者笔记
|
|---|
| mikeroyal/Photogrammetry-Guide | 10,083 | - 语言:
- Python
- 星标数:
- 1,529
- 分叉数:
- 111
- 简介:
- Photogrammetry Guide. Photogrammetry is widely used for Aerial surveying, Agriculture, Architecture, 3D Games, Robotics, Archaeology, Construction, Emergency management, and Medical.
|
|---|
| sjchoi86/dl_tutorials | 10,117 | - 星标数:
- 1,515
- 分叉数:
- 390
- 简介:
- Deep learning tutorials (2nd ed.)
|
|---|
| davidADSP/GDL_code | 10,130 | - 语言:
- Jupyter Notebook
- 星标数:
- 1,510
- 分叉数:
- 729
- 简介:
- The official code repository for examples in the O'Reilly book 'Generative Deep Learning'
|
|---|
| edmund-io/edmunds-claude-code | 10,131 | - 星标数:
- 1,510
- 分叉数:
- 277
|
|---|
| yeyun111/dlcv_for_beginners | 10,133 | - 语言:
- Python
- 星标数:
- 1,510
- 分叉数:
- 628
- 简介:
- 《深度学习与计算机视觉》配套代码
|
|---|
关键参数与规格
关键参数与规格| 参数 | 值 |
|---|
| 语言 | Jupyter Notebook |
|---|
| 类别 | Tutorials |
|---|
| 子类别 | ML/AI fundamentals,Math/CS fundamentals |
|---|
| 关键词 | Documentation, Education, Robotics |
|---|
| 星标数 | 1,524 |
|---|
| 分叉数 | 257 |
|---|
| 贡献者 | 1 |
|---|
| 创建日期 | 2020-12-17 |
|---|
| 更新日期 | 2026-10-14 |
|---|
| 1 天星标数 | 0 |
|---|
| 7 天星标数 | 7 |
|---|
| 排名 | 10,098 |
|---|
| 上次排名 | 5,641 |
|---|
| 排名变化 | -4,457 |
|---|
| 7 天星标排名 | 4,736 |
|---|
| 上次 7 天星标排名 | 4,749 |
|---|
| 7 天星标排名变化 | 13 |
|---|
| 总星标排名 | 8,000 |
|---|
| 上次总星标排名 | 7,987 |
|---|
| 总星标排名变化 | -13 |
|---|
| 国家 | USA |
|---|
README 摘录
Robotics 101: Computational Linear Algebra Computational Linear Algebra is a first-semester, first-year undergraduate course that shows how mathematics and computation are unified for reasoning about data and making discoveries about the world. The first iteration of the course ran in Fall 2020 at the University of Michigan Robotics Institute. Linear algebra and coding are rapidly becoming an essential foundation for the modern engineer in a computational world. Students in this course will gain insights into the mathematical theory
of linear algebra and its realization in practical computational tools. Math is the language of engineering, but coding is believing and realizing it. The mathematical content of ROB 101 is built around systems of linear equations, their representation as matrices, and numerical methods for their analysis. These methods will be given life through the lens of robotics and contemporary intelligent systems and their compelling applications. The entire course is available for the terms: Fall 2020 Fall 2021 And the homework
and projects: Fall 2022 & Winter 2023 Lecture, Recitation, and Lab Videos All lecture, recitation, and lab videos are available on YouTube: Fall 2020 videos Fall 2021 videos Lecture notes as well as recitation notes are also available in the repository. Textbook The textbook, Notes for Computational Linear Algebra, continues to be updated, and it is now available in LaTeX format in it's own GitHub repository. Projects Three main projects that accompany the course are available in the repository. Course Plan
Course plans for each term are in their respective repositories. Please let us know if anything is unclear. Course Evaluation Students thoughts on the courses can be read in the teaching evaluations. Credits Chad Jenkins, Associate Director of Undergraduate Programs, Michigan Robotics Jessy Grizzle, Director, Michigan Robotics Maani Ghaffari, Assistant Professor, Naval and Marine Architecture, U-M Kira Biener Tribhi Kathuria John Pye Madhav Achar Fangtong (Miley) Liu Shaoxiong Yao Eva Mungai Bruce JK Huang Grant A. Gibson Oluwami Dosunmu
-Ogunbi Lu Gan Ray Zhang License All code is licensed under the GNU General Public License v3. All other content, including textbooks, homeworks, and video, is licensed under the Creative Commons Attribution-NonCommericial 4. For more ROB 101 Course Information for those at U-M University of Michigan Robotics Michigan Robotics Twitter Michigan Robotics Instagram Behind the ROB 101 Course Philosophy
常见问题
记录了多少星标和分叉？
michiganrobotics/rob101 有 1,524 个星标和 257 个分叉。
仓库排名是多少？
michiganrobotics/rob101 排名第 10,098。
记录的语言和类别是什么？
michiganrobotics/rob101 有 1,524 个星标，语言为 Jupyter Notebook，类别为 Tutorials。
哪个仓库排名最接近？
michiganrobotics/rob101 与 mikeroyal/Photogrammetry-Guide 比较，后者排名第 10,083，有 1,529 个星标。
Robotics 101: Computational Linear Algebra
Computational Linear Algebra is a first-semester, first-year undergraduate course that shows how mathematics and computation are unified for reasoning about data and making discoveries about the world.
The first iteration of the course ran in Fall 2020 at the University of Michigan Robotics Institute.
Linear algebra and coding are rapidly becoming an essential foundation for the modern engineer in a computational world. Students in this course will gain insights into the mathematical theory of linear algebra and its realization in practical computational tools.
Math is the language of engineering, but coding is believing and realizing it. The mathematical content of ROB 101 is built around systems of linear equations, their representation as matrices, and numerical methods for their analysis. These methods will be given life through the lens of robotics and contemporary intelligent systems and their compelling applications.
The entire course is available for the terms:
And the homework and projects:
Lecture, Recitation, and Lab Videos
All lecture, recitation, and lab videos are available on YouTube:
Lecture notes as well as recitation notes are also available in the repository.
Textbook
The textbook, Notes for Computational Linear Algebra, continues to be updated, and it is now available in LaTeX format in it's own GitHub repository.
Projects
Three main projects that accompany the course are available in the repository.
Course Plan
Course plans for each term are in their respective repositories. Please let us know if anything is unclear.
Course Evaluation
Students thoughts on the courses can be read in the teaching evaluations.
Credits
- Chad Jenkins, Associate Director of Undergraduate Programs, Michigan Robotics
- Jessy Grizzle, Director, Michigan Robotics
- Maani Ghaffari, Assistant Professor, Naval and Marine Architecture, U-M
- Kira Biener
- Tribhi Kathuria
- John Pye
- Madhav Achar
- Fangtong (Miley) Liu
- Shaoxiong Yao
- Eva Mungai
- Bruce JK Huang
- Grant A. Gibson
- Oluwami Dosunmu-Ogunbi
- Lu Gan
- Ray Zhang
License
All code is licensed under the GNU General Public License v3.0.
All other content, including textbooks, homeworks, and video, is licensed under the Creative Commons Attribution-NonCommericial 4.0 (CC BY-NC 4.0).
For more