2023-AIKU_DeepLearning-Bootcamp

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2023-AIKU_DeepLearning-Bootcamp

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2023-1 고려대학교 AIKU 딥러닝 방학 부트캠프: Deep into Deep

2023-AIKU_DeepLearning-Bootcamp 최신버젼 다운로드

최종 버전 다운로드 (.zip)

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# 2023-AIKU_DeepLearning-Bootcamp
![](https://raw.githubusercontent.com/ONground-Korea/2023-AIKU_DeepLearning-Bootcamp/main/logo.png)
2023-AIKU_DeepLearning-Bootcamp is the material (lecture notes, exercises and assignments) repository for learning and experiencing various deep learning and its applications with PyTorch at Korea University AIKU.

## Contents
- **1. Machine Learning and MLP** - [Seongchan Kim](https://github.com/deep-overflow)
  - [[Lecture 1]](https://github.com/ONground-Korea/2023-AIKU_DeepLearning-Bootcamp/blob/main/Lectures/1.%20Machine%20Learning%20and%20MLP.pdf)
  - [[Exercise]](https://github.com/ONground-Korea/2023-AIKU_DeepLearning-Bootcamp/blob/main/Exercises/1.%20Machine%20Learning%20and%20MLP.ipynb)
  - [[Assignment #1]](https://github.com/ONground-Korea/2023-AIKU_DeepLearning-Bootcamp/blob/main/Assignments/1.%20Machine%20Learning%20and%20MLP.ipynb)
- **2. CNN and CNN Architectures** - [Honggyu An]()
  - [[Lecture 2]](https://github.com/ONground-Korea/2023-AIKU_DeepLearning-Bootcamp/blob/main/Lectures/2.%20CNN%20and%20CNN%20Architecture.pdf)
  - [[Assignment #2: Implementation of AlexNet and VGG16]](https://github.com/ONground-Korea/2023-AIKU_DeepLearning-Bootcamp/blob/main/Assignments/2.%20CNN%20and%20CNN%20Architectures.ipynb)
- **3. Object Detection and Segmentation** - [Jisang Han](https://github.com/ONground-Korea)
  - [[Lecture 3]](https://github.com/ONground-Korea/2023-AIKU_DeepLearning-Bootcamp/blob/main/Lectures/3.%20Object%20Detection%20and%20Segmentation.pdf)
  - [[Assignment #3: Impelment Custom Dataset and Fintune Faster RCNN]](https://github.com/ONground-Korea/2023-AIKU_DeepLearning-Bootcamp/tree/main/Assignments/3.%20Object%20Detection%20and%20Segmentation)
- **4. RNN and Attention** - [Seongyun Lee](https://github.com/sylee0520)
  - [[Lecture 4]](https://github.com/ONground-Korea/2023-AIKU_DeepLearning-Bootcamp/blob/main/Lectures/4.%20RNN%20and%20Attention.pdf)
  - [[Assignment 4]](https://github.com/ONground-Korea/2023-AIKU_DeepLearning-Bootcamp/blob/main/Assignments/4.%20RNN%20and%20Attention.ipynb)
- **5. Natural Language Processing** - [Seongyun Lee](https://github.com/sylee0520)
  - [[Lecture 5]](https://github.com/ONground-Korea/2023-AIKU_DeepLearning-Bootcamp/blob/main/Lectures/5.%20Natural%20Language%20Processing.pdf)
  - [[Assignment 5]](https://github.com/ONground-Korea/2023-AIKU_DeepLearning-Bootcamp/blob/main/Assignments/5.%20Natural%20Language%20Processing.ipynb)
- **6. 3D Vision and Videos** - [Jisang Han](https://github.com/ONground-Korea)
  - [[Lecture 6]](https://github.com/ONground-Korea/2023-AIKU_DeepLearning-Bootcamp/tree/main/Lectures/6.%203D%20Vision%20and%20Videos)
  - [[Assignment 6]]()
- **7. Generative Models** - [Jisang Han](https://github.com/ONground-Korea)
  - [[Lecture 7]](https://github.com/ONground-Korea/2023-AIKU_DeepLearning-Bootcamp/blob/main/Lectures/7.%20Generative%20Models.pdf)
  - [[Assignment 7]](https://github.com/ONground-Korea/2023-AIKU_DeepLearning-Bootcamp/tree/main/Assignments/7.%20Generative%20Models)

More information is available at [curriculum.md](https://github.com/ONground-Korea/2023-AIKU_DeepLearning-Bootcamp/blob/main/curriculum.md)
## References
- [EECS 498-007 / 598-005](https://www.youtube.com/watch?v=dJYGatp4SvA&list=PL5-TkQAfAZFbzxjBHtzdVCWE0Zbhomg7r)
- [CS231n](https://www.youtube.com/watch?v=vT1JzLTH4G4&list=PLC1qU-LWwrF64f4QKQT-Vg5Wr4qEE1Zxk)
- COSE474 김승룡 교수님 딥러닝 강의

## License

The class is licensed under the [MIT License](http://opensource.org/licenses/MIT):

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

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