# Coursera-Deep-Learning-deeplearning.ai **Repository Path**: tlkt/Coursera-Deep-Learning-deeplearning.ai ## Basic Information - **Project Name**: Coursera-Deep-Learning-deeplearning.ai - **Description**: （完结）网易云课堂微专业《深度学习工程师》听课笔记，编程作业和课后练习 - **Primary Language**: Unknown - **License**: MIT - **Default Branch**: master - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 3 - **Forks**: 1 - **Created**: 2020-01-23 - **Last Updated**: 2025-11-08 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README

网易云课堂微专业-Andrew Ng《深度学习》课后练习编程作业和笔记

该仓库包含本课程的所有笔记内容，和课程练习，我珍惜这门课的每一节课，通过对知识的整理能够加深对知识的理解，也通过整理的内容为有需要的童鞋提供些许帮助！！ *欢迎 Star* [网易云课堂](http://study.163.com/) 提供的免费正版的课程资料，给予了我极大的帮助。 ## [博客传送门](https://alberthg.github.io/tags/#deeplearning.ai) ## 笔记 - [神经网络与深度学习](https://github.com/AlbertHG/Coursera-Deep-Learning-deeplearning.ai/tree/master/01-Neural%20Networks%20and%20Deep%20Learning) - [神经网络的基础](https://github.com/AlbertHG/Coursera-Deep-Learning-deeplearning.ai/tree/master/01-Neural%20Networks%20and%20Deep%20Learning/week2) - [浅层神经网络](https://github.com/AlbertHG/Coursera-Deep-Learning-deeplearning.ai/tree/master/01-Neural%20Networks%20and%20Deep%20Learning/week3) - [深层神经网络](https://github.com/AlbertHG/Coursera-Deep-Learning-deeplearning.ai/tree/master/01-Neural%20Networks%20and%20Deep%20Learning/week4) - [改进深度神经网络：超参数调整，正则化和优化](https://github.com/AlbertHG/Coursera-Deep-Learning-deeplearning.ai/tree/master/02-Improving%20Deep%20Neural%20Networks%20Hyperparameter%20tuning%2C%20Regularization%20and%20Optimization) - [深度学习的实用层面](https://github.com/AlbertHG/Coursera-Deep-Learning-deeplearning.ai/tree/master/02-Improving%20Deep%20Neural%20Networks%20Hyperparameter%20tuning%2C%20Regularization%20and%20Optimization/week1) - [优化算法](https://github.com/AlbertHG/Coursera-Deep-Learning-deeplearning.ai/tree/master/02-Improving%20Deep%20Neural%20Networks%20Hyperparameter%20tuning%2C%20Regularization%20and%20Optimization/week2) - [超参数调试、Batch 正则化和程序框架](https://github.com/AlbertHG/Coursera-Deep-Learning-deeplearning.ai/tree/master/02-Improving%20Deep%20Neural%20Networks%20Hyperparameter%20tuning%2C%20Regularization%20and%20Optimization/week3) - [结构化机器学习项目](https://github.com/AlbertHG/Coursera-Deep-Learning-deeplearning.ai/tree/master/03-Structuring%20Machine%20Learning%20Projects) - [卷积神经网络](https://github.com/AlbertHG/Coursera-Deep-Learning-deeplearning.ai/tree/master/04-Convolutional%20Neural%20Networks) - [卷积神经网络基础](https://github.com/AlbertHG/Coursera-Deep-Learning-deeplearning.ai/tree/master/04-Convolutional%20Neural%20Networks/week1) - [深度卷积网络：实例探究](https://github.com/AlbertHG/Coursera-Deep-Learning-deeplearning.ai/tree/master/04-Convolutional%20Neural%20Networks/week2) - [目标检测](https://github.com/AlbertHG/Coursera-Deep-Learning-deeplearning.ai/tree/master/04-Convolutional%20Neural%20Networks/week3) - [特殊应用：人脸识别和神经风格转换](https://github.com/AlbertHG/Coursera-Deep-Learning-deeplearning.ai/tree/master/04-Convolutional%20Neural%20Networks/week4) - [序列模型](https://github.com/AlbertHG/Coursera-Deep-Learning-deeplearning.ai/tree/master/05-Sequence%20Models) - [循环神经网络(RNN)](https://github.com/AlbertHG/Coursera-Deep-Learning-deeplearning.ai/tree/master/05-Sequence%20Models/week1) - [自然语言处理与词嵌入](https://github.com/AlbertHG/Coursera-Deep-Learning-deeplearning.ai/tree/master/05-Sequence%20Models/week2) - [序列模型和注意力机制](https://github.com/AlbertHG/Coursera-Deep-Learning-deeplearning.ai/tree/master/05-Sequence%20Models/week3) ## 课程地址 [deeplearning.ai - 网易云课堂 - 深度学习工程师微专业](https://study.163.com/provider/2001053000/index.htm) ## 参考项目 在整理自己的笔记的时候，从下列道友中参考了很多内容，谢之： * [红色石头的机器学习之路](https://zhuanlan.zhihu.com/Redstone) * [机器学习之路](https://zhuanlan.zhihu.com/koalatree) * [KyonHuang-吴恩达《深度学习》系列课程笔记](http://kyonhuang.top/Andrew-Ng-Deep-Learning-notes/#/) ## 备注 - GitHub 的 README.md 文件不提供 LaTeX 公式解析，可使用 chrome 浏览器插件[GitHub with MathJax](https://chrome.google.com/webstore/detail/github-with-mathjax/ioemnmodlmafdkllaclgeombjnmnbima) - 由于 Github 中的文件大小限制规则，编程练习中缺少的数据集文件可以从对应文件夹里边的".gitignore"文件中得知。或者在下方下载完整的作业包。 ## 作业包 神经网络与深度学习 - [Class1-Week2-神经网络的基础](https://stu2013jnueducn-my.sharepoint.com/:f:/g/personal/hhhgggpps_stu2013_jnu_edu_cn/EpAz0IkD8ZJFgd9JFjs5-50BR7P0mBLVcEwhEofD0A9Rzw?e=1USVVD) - [Class1-Week3-浅层神经网络](https://stu2013jnueducn-my.sharepoint.com/:f:/g/personal/hhhgggpps_stu2013_jnu_edu_cn/EuzaPNhIaotBrurYhJH2z7gBzMxlu-J9BrMNNYF3P8efhA?e=1BX6ht) - [Class1-Week4-深层神经网络](https://stu2013jnueducn-my.sharepoint.com/:f:/g/personal/hhhgggpps_stu2013_jnu_edu_cn/EmRlwB2RJrVEuH8ddjqJoogBWm498PA58TcINJF5W8x9xA?e=Wm6Oeo) 改进深度神经网络：超参数调整，正则化和优化 - [Class2-Week1-深度学习的实用层面](https://stu2013jnueducn-my.sharepoint.com/:f:/g/personal/hhhgggpps_stu2013_jnu_edu_cn/Et1y993iHHdMm9lN-7iG4gwBsucuZ8vOVEpO-8EkwvsJ8Q?e=54sg8L) - [Class2-Week2-优化算法](https://stu2013jnueducn-my.sharepoint.com/:f:/g/personal/hhhgggpps_stu2013_jnu_edu_cn/EjtGojLKuMRLsm6KJdciIx8BRQUdwa6ngK-cGR3eEJnhIg?e=bvZ9NQ) - [Class2-Week3-超参数调试、Batch 正则化和程序框架](https://stu2013jnueducn-my.sharepoint.com/:f:/g/personal/hhhgggpps_stu2013_jnu_edu_cn/EgKFXlPAde9IoSUYVHoA8xABYoyl3B-o8W7qjTNcM4eFfQ?e=gYJD58) 卷积神经网络 - [Class4-Week1-卷积神经网络基础](https://stu2013jnueducn-my.sharepoint.com/:f:/g/personal/hhhgggpps_stu2013_jnu_edu_cn/EqFrAVrvHZBNkN0Z6jyILykB8BhF24MLk5P4zP7yKgVyUA?e=tLmGaX) - [Class4-Week2-深度卷积网络：实例探究](https://stu2013jnueducn-my.sharepoint.com/:f:/g/personal/hhhgggpps_stu2013_jnu_edu_cn/EuNiXQ2VYBlCoUIRCVJc1QUBUdnAHRb6VP6k6nLpxvk86g?e=rsp6HH) - [Class4-Week3-目标检测](https://stu2013jnueducn-my.sharepoint.com/:f:/g/personal/hhhgggpps_stu2013_jnu_edu_cn/EgrReZ4wCcRKssRAx3QLE4gBXsH9-tUF_Y8Pms-_x235cQ?e=SwmUki) - [Class4-Week4-特殊应用：人脸识别和神经风格转换](https://stu2013jnueducn-my.sharepoint.com/:f:/g/personal/hhhgggpps_stu2013_jnu_edu_cn/Eocx2TcfHlhAlw15qd_GY6wBlu38O7-xIgNNv4Eh3ooU7A?e=yY2okb) 序列模型 - [Class5-Week1-循环神经网络(RNN)](https://stu2013jnueducn-my.sharepoint.com/:f:/g/personal/hhhgggpps_stu2013_jnu_edu_cn/EjAxMUxkSWJPhChFFdNinOkBrveKcu2XrpZwtUKTfsRo1g?e=GDAXdi) - [Class5-Week2-自然语言处理与词嵌入](https://stu2013jnueducn-my.sharepoint.com/:f:/g/personal/hhhgggpps_stu2013_jnu_edu_cn/EpYQTM__FThClHISMeBIZ08BWePqw-7Ul8z5oTkhh3_RLA?e=IdthX7) - [Class5-Week3-序列模型和注意力机制](https://stu2013jnueducn-my.sharepoint.com/:f:/g/personal/hhhgggpps_stu2013_jnu_edu_cn/Eom2rvlZ1vBKg8Yoa5IqBR4BZFAIxmXHgShxcbAhTg-VMw?e=7zCCYB) ## License 遵循 MIT 许可证。有关详细，请参阅 [LICENSE](https://github.com/AlbertHG/Coursera-Deep-Learning-deeplearning.ai/blob/master/LICENSE)。