本项目是我个人学习《动手学深度学习 v2》课程的代码分享。内容主要参考了《动手学深度学习 v2》这本书，从零开始介绍深度学习算法和代码实现。
This project contains my code sharing for learning the "Dive into Deep Learning v2" course. The content primarily references the book "Dive into Deep Learning v2", which introduces deep learning algorithms and code implementations from scratch.
- 课程主页: 动手学深度学习 v2
- 教材: 动手学深度学习 v2
- Course Homepage: Dive into Deep Learning v2
- Textbook: Dive into Deep Learning v2
《动手学深度学习 v2》是一本面向中文读者的深度学习教科书，涵盖了深度学习的基础理论和实践应用。本书不仅提供了详细的算法讲解，还提供了丰富的代码实现，帮助读者在实际数据上获得第一手经验。
"Dive into Deep Learning v2" is a textbook for Chinese readers that covers the foundational theories and practical applications of deep learning. The book not only provides detailed explanations of algorithms but also offers rich code implementations to help readers gain hands-on experience with real data.
- 从零开始: 适合初学者，不需要深厚的数学和编程背景。
- 详细讲解: 结合文字、公式和图示，详细讲解深度学习的常用模型和算法。
- 代码实现: 提供从零开始实现深度学习模型的代码示例，使用PyTorch、NumPy/MXNet、TensorFlow和PaddlePaddle等多种框架。
- 实战经验: 通过实际数据和项目，帮助读者积累深度学习的实战经验。
- From Scratch: Suitable for beginners with no deep background in mathematics or programming.
- Detailed Explanations: Combines text, formulas, and diagrams to provide detailed explanations of commonly used deep learning models and algorithms.
- Code Implementations: Offers code examples to implement deep learning models from scratch using multiple frameworks such as PyTorch, NumPy/MXNet, TensorFlow, and PaddlePaddle.
- Practical Experience: Helps readers gain practical experience through real data and projects.
- 阅读教材: 从教材开始，逐章学习深度学习的基础知识和算法。
- 观看课程视频: 在课程主页上观看课程视频，跟随讲师的讲解加深理解。
- 动手实践: 在每章的练习中，动手实现代码，加深对算法的理解和应用。
- 参与社区讨论: 通过每章最后的链接，加入社区讨论，与其他学习者交流心得和问题。
- Read the Textbook: Start with the textbook and learn the foundational knowledge and algorithms of deep learning chapter by chapter.
- Watch Course Videos: Watch the course videos on the course homepage to deepen your understanding by following the instructor's explanations.
- Hands-on Practice: Implement the code in the exercises at the end of each chapter to deepen your understanding of the algorithms.
- Join Community Discussions: Join community discussions through the links at the end of each chapter to exchange ideas and solve problems with other learners.
- data: 存放数据集
- notebooks: 存放Jupyter笔记本文件，包含每章的代码实现
- models: 存放训练好的模型
- data: Stores datasets
- notebooks: Contains Jupyter notebook files with code implementations for each chapter
- models: Stores trained models
如果有任何问题或建议，欢迎联系我。邮箱: [tenny314159@gmail.com]
If you have any questions or suggestions, feel free to contact me. Email: [tenny314159@gmail.com]
希望这个项目对你有所帮助，祝你学习愉快！
I hope this project is helpful to you and wish you a pleasant learning experience!