deeplearning.ai-note
- 本仓库deeplearning.ai-note由双愚整理， Fork或借鉴请注明出处 @双愚 . Thx
吴恩达在Coursera上推出的“深度学习专项课程“引起了一波AI学习热潮，而自发布以来，国内学习者对于课程汉化的呼声也从未停止。前些天，网易云课堂终于官方发布了经过授权的汉化课程
- 更多资料分享和技术交流，可加入吴恩达深度学习交流群：680932474
- 黄海广博士的资源汇总
- 何宽 - 【deplearning.ai】【吴恩达课后作业汇总】- CSDN
- (荐)中文版Quiz测试题
- 代码讲解视频(bilibili): https://space.bilibili.com/10410626
视频
- (荐)哔哩哔哩up上传中英字幕课程：https://space.bilibili.com/288630933
- 网易云视频教程地址：https://mooc.study.163.com/university/deeplearning_ai#/c
- Coursera视频（收费，不过可以申请免费）：https://www.coursera.org/specializations/deep-learning
笔记在线阅读http://www.ai-start.com/dl2017
深度学习专项课程(Deep Learning Specialization on Coursera)
Course 1. 神经网络和深度学习 Neural Networks and Deep Learning
- Week1 - [第一周：深度学习引言(Introduction to Deep Learning)]
- Week2 - [第二周：神经网络的编程基础(Basics of Neural Network programming)]
- Week3 - [第三周：浅层神经网络(Shallow neural networks)]
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Week4 - [第四周：深层神经网络(Deep Neural Networks)]
Course 2. 改善深层神经网络 Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization
- Week1 - [第一周：深度学习的实用层面(Practical aspects of Deep Learning)]
- Setting up your Machine Learning Application
- Regularizing your neural network
- Setting up your optimization problem
- Week2 - [第二周：优化算法 (Optimization algorithms)]
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Week3 - [第三周超参数调试，batch正则化和程序框架（Hyperparameter tuning, Batch Normalization and Programming Frameworks)]
Course 3. 结构化机器学习项目 Structuring Machine Learning Projects
- Week1 - [第一周：机器学习策略（1）(ML Strategy (1))]
- Setting up your goal
- Comparing to human-level performance
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Week2 - [第二周：机器学习策略（2）(ML Strategy (2))]
- Error Analysis
- Mismatched training and dev/test set
- Learning from multiple tasks
- End-to-end deep learning
Course 4. 卷积神经网络 Convolutional Neural Networks
- Week1 - [第一周 卷积神经网络(Foundations of Convolutional Neural Networks)]
- Week2 - [第二周 深度卷积网络：实例探究(Deep convolutional models: case studies)](
- Week3 - [第三周 目标检测（Object detection）]
- Week4 - [第四周 特殊应用：人脸识别和神经风格转换（Special applications: Face recognition &Neural style transfer）]
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Course 5. 序列模型 Sequence Models
- Week1 - [Recurrent Neural Networks]
- Week2 - [Natural Language Processing & Word Embeddings]
- Week3 - [Sequence models & Attention mechanism]
目录结构
├─01神经网络和深度学习 │ ├─Code编程作业 │ └─Quiz测验题 ├─02改善深度神经网络 │ ├─Code编程作业 │ └─Quiz测验题 ├─03结构化机器学习项目 │ ├─Code编程作业 │ └─Quiz测验题 ├─04卷积神经网络 │ ├─Code编程作业 │ └─Quiz测验题 ├─05序列模型 │ ├─Code编程作业 │ └─Quiz测验题
可学习参考资料
- 笔记在线阅读
- http://blog.csdn.net/hdhuangzhihao
- http://blog.csdn.net/justry24/article/category/7159918
- http://blog.csdn.net/koala_tree/article/category/7186915
- http://blog.csdn.net/weixin_37993251
- http://blog.csdn.net/hongbin_xu/article/category/7323091
- http://blog.csdn.net/junjun_zhao【有自己的注解】
- https://blog.csdn.net/u013733326/article/details/79827273 别人汇总的作业博客
TO DO
持续更新中... ...
更多可参考
- Kulbear/deep-learning-coursera
- greebear/deeplearning.ai-notes
- greebear/deeplearning.ai-notes
- https://github.com/greebear/deeplearning.ai-notes
开源许可证 License MIT
- 开源是一种精神，MachineLearning_Ng的开源更是人的一种进步
- 开源是自由的，而不是免费的。Free(自由) is not free(免费) 请认真阅读并遵守以下开源协议 License MIT
此外，代码仅作学习深度学习专项课程(Deep Learning Specialization on Coursera)所用，代码和笔记禁止私用，违者必究
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