Wu Enda DeepLearning.ai "Deep Learning" course notes

Transfer from: https://blog.csdn.net/koala_tree/article/details/79913655


Author : Mr. tree
blog : http://blog.csdn.net/koala_tree
know almost : https://www.zhihu.com/people/dashuxiansheng
GitHub : https://github.com/KoalaTree
2018 April 5, day


This article published in the know almost column, for the convenience of users accustomed to using CSDN, change the linear notes to the following article in the CSDN.
At the same time, I also welcome everyone to pay attention to my knowledge: Mr. Dashu, there will be new dry goods updates from time to time. Learn together and make progress together! ^_^


Introduction to DeepLearning.ai

deepLearning.ai is a series of courses on teaching deep learning launched by Wu Enda on Coursera. The whole topic includes five courses: 01. Neural Networks and Deep Learning; 02. Improving Deep Neural Networks-Hyperparameter Tuning, Regularization and Optimization; 03. Structured Machine Learning Projects; 04. Convolutional Neural Networks; 05. Sequences model.

Course Description:

Allow me to quote the introduction of the official website:

If you want to get into artificial intelligence, this course topic will help you. Deep learning is one of the most sought-after skills in the field of technology, and we will help you learn this knowledge.
In the five courses, you will learn the basics of deep learning, understand how to build neural networks, and learn how to practice machine learning projects, learn convolutional networks, RNN, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, etc. . You will work on case studies in medical treatment, autonomous driving, sign language reading, music creation and natural language processing. By then, you will not only master the basic theories of deep learning, but also see its applications in industry. The above ideas will be implemented in Python and TensorFlow exercises. In addition, you will also hear many senior leaders in deep learning who will share their personal stories with you and provide you with career advice.
AI is having a huge impact on all walks of life. After completing the courses on this topic, you may find creative ways to apply it to your work. We will help you master deep learning, understand how to use it, and help you build a career in AI.

Course content:

  • Coursera : Official course schedule (English subtitles). Paying users can get homework grades in coursework, and get a certificate of completion for each course; they can take classes and do homework for free without paying, but they can’t get a course certificate if they don’t have homework grades.
  • NetEase Cloud Classroom : Genuine license introduced by NetEase (Chinese and English subtitles). The courses are completely free, but there are no homework and no course certificates.

Recommended:

4.5 stars (personal opinion) a
rare good course among the existing deep learning courses.

Collection of personal refining notes and programming assignments

The following are the main notes extracted from the individual in the course of class, as well as the programming homework completed by himself. Courses are the main course, exercises are supplemented, and notes are used to consolidate . So I suggest that you use this core idea to study this course. Not much nonsense, take notes!


01. Neural Networks and Deep Learning


02. Improve deep neural network: hyperparameter debugging, regularization and optimization


03. Structured Machine Learning Project


04. Convolutional Neural Network


05. Sequence Model

to sum up

The learning span of the whole thematic course is relatively long, and the process of constantly thinking and taking notes during the class is indeed slow and hard, but it does have a lot of gains along the way. At the beginning, I just made a note for later review, but later I felt that the recorded notes were still neat, so I put it on Zhihu and shared it with everyone. I hope that these of mine can be given to more students and friends with the same needs. Bring a little help.

At last

Note is a refinement of the course. Although it is generally more comprehensive, it is limited to the individual's ability and energy. Omissions or errors will inevitably appear in the notes. If you find the wrong place while reading the notes and the content that I think is more important but I did not record, then you are welcome to leave a comment or private message to me below, I will make corrections and supplements in time, thank you for your support.

Finally, I would like to thank every friend who liked it. At the same time, other platforms are also welcome to reprint and share, and make progress together ^_^!

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Origin blog.csdn.net/yyyllla/article/details/88582744