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)
神经网络和深度学习 Neural Networks and Deep Learning
Course 1.- 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)]
- Week4 - [第四周:深层神经网络(Deep Neural Networks)]
改善深层神经网络 Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization
Course 2.- 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)]
- 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)]
结构化机器学习项目 Structuring Machine Learning Projects
Course 3.- Week1 - [第一周:机器学习策略(1)(ML Strategy (1))] - Setting up your goal - Comparing to human-level performance
- 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
卷积神经网络 Convolutional Neural Networks
Course 4.- 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)]
序列模型 Sequence Models
Course 5.- 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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