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Learning summary (about deep learning, vision and learning experience)

2020-11-08 09:45:19 osc_sqtwbty4

It's today 2020 year 11 month 6 Japan , It's been a month since I came to Shanghai , I want to write a summary of my study , Then I started to try new ways of learning .

Catalog

Learning material sharing

of python Study

of OpenCV+python Computer vision image processing learning

On neural network learning

About deep learning basic learning  

Partial theory

  Biased practice

On frame learning

Keras

tensorflow

Pytorch

Thinking method

Based on learning

solve the problem

New ideas and inspiration

expectation  

Summary


2020 year 3 Computer vision begins in January , Contact keras frame , A lot of them didn't understand at that time , Bit by bit , Finally, I successfully completed my first visual project, which is my graduation project 《 Design and implementation of facial expression recognition system based on convolutional neural network 》. Now simply recall the learning process at that time , By the way, I'd like to summarize a little bit of experience , I hope it will be helpful to the students at the beginning , Come on together ( Some learning videos may not be very classic , But it was my own choice, consciously or unconsciously , Therefore, it is only for reference ).

Learning material sharing

of python Study

First contact python Is in 2018 year 10 month , At that time, a person was painting videos in the undergraduate laboratory during the National Day holiday , Make notes , Crazy input . What we learn is 《[ Little turtle ] Basic learning Python》, Unfortunately, it was not fully used at that time CSDN Blog , I wrote down all the notes in the Word file , A lot of records , It's a bit messy . It's a bit stupid to take notes at first , A lot of them , At the same time, it also taps the code , Keep trying 、 Errors and Solutions . Sometimes encounter fun will also write their own code to amuse themselves ( This is a screenshot of the circle of friends ).

B Station links :https://b23.tv/kLRXOX ( Partial contents and screenshots )

 

of OpenCV+python Computer vision image processing learning

Originally in B I've learned from you once , A video to get me started 《OpenCV+python Computer vision image processing 》, I started taking notes by hand, but I found it was too slow , We found that the video code was pasted in the video introduction , Download and learn quickly . Follow the video to configure the required environment , Follow the video and comment on the code provided , Write your own understanding . It used to be using Typora This kind of Markdown Editor to take notes , After a period of time, it should be that I didn't master it well ( The picture reprint aspect appears the problem, has been dragging has not solved ), It's right there CSDN To take notes ( See the screenshot of the column below ).

B Station links :https://www.bilibili.com/video/BV1QJ411W7SS?p=1 ( Partial contents and screenshots )

Screenshot of column ( Some notes at that time are arranged here , Later, I learned something about it and kept it , It may be a bit messy in some places , Your smile .)

There are also some quality book resources as follows :

link :https://pan.baidu.com/s/1rAzNRaJSe8EwxWVVTCQp6g Extraction code :i924

On neural network learning

We need to be a learning power every day , At that time, I saw what was said by Chen Bin, a teacher of Peking University 《 Artificial intelligence and information society 》( Partial theory , Consider getting started ),

I just started studying in a powerful country , Later it was found that there was no double speed , A little sad , Went directly to the corresponding MOOCS to learn , It's great to find MOOCS , You can also download the corresponding PPT, I wrote some notes in the blog column 《 Notes on learning neurons and neural networks 》

MOOC link :https://www.icourse163.org/course/0809PKU037-1003471009

About deep learning basic learning  

Partial theory

I learned from Wu Enda , It was B Station learning , It was later found that Netease cloud classroom has courses . Overall, I felt very good , The teacher said it over and over again , Suitable for entry , Partial theory . Just started taking notes by taking screen shots , It's too slow to find out , I accidentally found that Mr. Huang haiguang wrote a complete set for this course 《DeepLearning.ai In depth learning course notes 》 And always updated , What's up to date with me now 5.7 edition . I also made my own notes based on the video presentation and course notes , Although many of them are copy and paste , But I still want to do it , Do some highlights and occasional summaries , This is more profound .( Address of Wu Enda's in depth learning notes column :https://blog.csdn.net/dujuancao11/category_9871211.html , It is suggested that you watch the video and take notes , I write a simple look at the line , I'm for the convenience of my own review .)

Netease cloud classroom link :https://mooc.study.163.com/smartSpec/detail/1001319001.htm

Cover of supporting notes and screenshots of some contents :

link :https://pan.baidu.com/s/142Lj7n5hneg-VgjgkM7fvg Extraction code :tj40 

  Biased practice

After learning Wu Enda's deep learning course , I learned 《 Hands-on deep learning Pytorch edition 》, This time, I have a deeper understanding of some basic things in-depth learning , And it's more about using Pytorch Framework to implement , Not only deepen the understanding of the foundation of deep learning , And it's easy to learn Pytorch Basic syntax .

Some catalogues and Book screenshots

Corresponding source code :https://github.com/ShusenTang/Dive-into-DL-PyTorch

Network disk link :https://pan.baidu.com/s/1HdATN4RZxdEDZbCtSrPUdw Extraction code :z66y

On frame learning

Keras

The first frame I used was keras( You can put Keras regard as tensorflow After the encapsulation API), There is a corresponding official document, and there is one PDF file .

Keras Chinese document :https://keras.io/zh/

Screen capture of document section :

Network disk link :https://pan.baidu.com/s/1BVBjLTi0UGtP_VVkIzwVLw Extraction code :1145 

tensorflow

Simple contact , Use Keras When you need it , I've written a few blog posts about it before .

tensorflow Entry variable constant :https://blog.csdn.net/dujuancao11/article/details/104896330

3tensorflow arithmetic :https://blog.csdn.net/dujuancao11/article/details/105051971

The biggest headache should be tensorflow-gpu Configuration of Well , In this post :《 Virtual environment installation 》https://blog.csdn.net/dujuancao11/article/details/107468687 ( There are a lot of things , It may be a bit messy )

You can also read this one :《 of Python Simple installation of some commonly used software ( Baidu disk installation package link attached )》https://blog.csdn.net/dujuancao11/article/details/109394751

And in Problems in configuration :《tf-gpu( testing 、np.dtype([(“qint8“, np.int8, 1)]) 、 not compiled to use: AVX2、CUDNN_STATUS_ALLOC_FAILED)》https://blog.csdn.net/dujuancao11/article/details/109111198

Pytorch

In fact, this framework is mainly based on 《 Hands-on deep learning Pytorch edition 》 In contact with , There is no specialized study yet , But there are also learning documents 《PyTorch Official course in Chinese 》.

Network disk link :https://pan.baidu.com/s/1k9XrhuPI3nFJP8tweNrLsQ Extraction code :w6ve

Summary

The above recommendations PyTorch

The above are some of the materials I used in the learning process , Complete Baidu disk link :https://pan.baidu.com/s/1ygkz4rv2nZQrnn86i4Weyw Extraction code :5u7y

Thinking method

Based on learning

  1. Based on learning : promote Search for information The ability of , Learn to learn to stand on the shoulders of giants , Learn to search the corresponding source code 、 E-books and PPT etc. .
    Some sources :CSDN、B standing 、 WeChat official account 、 You know 、 Simple books ( Serious exploration will find learning power is also good , For example, new developments in a certain field 、 The new policy , Facilitate better decision making .)
    I have to admit that there are many excellent people around here doing official account. B Stop video , For example, I love WeChat official account. : Handsome play with programming Gongzilong OAOA( My high school classmates ) etc. ,CSDN Blogger :
    Bubbliiiing( It's really Example ).
    The paper : I read too little , The next goal is to read the paper well .



  2. note :  It's necessary to take notes yourself , Choose your own way to take notes , For example, I'm used to it CSDN Blog notes , Although sometimes it's just a simple copy and paste , But I'm going to do it again , Bold and red in some places , Write your own thoughts in some places 、 Summary or doubt . Take notes in time , Wrote a lot of blogs , Start to be strict with yourself , Although it is still far from the target .
    Possible problems :
    1) To solve a problem , I read too much information , But there are some gains , No time to take notes , You can choose the key points to take notes , You can also focus on a time to write .
    2) Blog errors may occur , Because they are basically self-taught , It is inevitable that there will be a lack of understanding , Boldly remember , Continuous updating and modification .( If there is a mistake in my blog , Welcome to point out , Come on together . But don't be too demanding , Time and energy are limited , I write as well as I can . Thank you for your support !)
    3) There are some relatively new ideas , With protection in mind , May be set to private .



  3. communication : And mentors 、 There are also excellent students to communicate with each other , A lot of inspiration , Cherish everything now .

solve the problem

  1. State of mind : I think we must have a good attitude , Download a software 、 Configuration environment 、 Write code 、 Debugging and running problems are too normal , Don't be afraid of trouble , Facing problems , Learn to search and solve by yourself . A lot of times, there's a problem , A solution others can , You can't and it's normal , Just try more ( It's right to have a good time ).
  2. Get from the problem inspire
    example 1: I didn't know anything at the beginning of deep learning , Direct use CPU Training Fer2013 Data sets and Inception The Internet , Training speed moving , Too slow , Only later did I know it could be used GPU Speed up ( Have you read this article :https://zhuanlan.zhihu.com/p/30751437), Also know the need to support training graphics card can ( Graphic card calculator https://developer.nvidia.com/cuda-gpus), Later he learned to configure Tensorflow-gpu.

    example 2: A little accident , There is no sound in the video recording , Thinking about putting the PPT Intercept it ,1 An hour of video , It's too slow to intercept one by one , A smart machine opencv Try it . See my blog for details :https://blog.csdn.net/dujuancao11/article/details/109404108


New ideas and inspiration

  1. Take part in more Academic Conference , Last time CGCKD( Organized by Shanxi University 2020 Chinese Symposium on Granular Computing and knowledge discovery ( The 20th China Rough Conference on set and soft computing 、 The 14th China Granular Computing Conference 、 The eighth academic conference on three branches of decision making )), The biggest learning is : At present, artificial intelligence is based on computation , Next stage based on memory . I also feel the teachers' love and passion for academic , An example of learning , I hope that one day we can become as excellent scientific researchers as they are , Do things in a down-to-earth manner .
  2. actual : We should be good at connecting what we have learned in real life , It has a certain sensitivity , I think the ultimate goal of scientific research is to serve the society , Service provider itself .
  3. Be good at understanding some policies or disciplines dynamic , Convenient and better decision making .

expectation  

Writing this blog is also to end this stage of learning , Try to start a new learning method .

  1. Work and rest more regularly , Keep early hours .
  2. Be more self disciplined , Exercise on running ( Exercise is also creating conditions for scientific research ).
  3. More planning for study .
  4. Be more modest ( I've always been cai, It's far from the target ).
  5. hope xiyu Deo gratias , Come on together !

Summary

That's the end of sharing , A little experience , In fact, it is “ come clean ” The share of , I'm under a lot of pressure , Because I'm exploring a lot of places , Not very well . But I'm still willing to sort out the fragmented learning links before , Spend hours writing this blog post . Thank you for everything now , Appreciate support and like ( As of now 484 Fans ), I'll work harder to blog .

I spent a whole month in graduate school , Like school , Teachers met 、 Senior brothers and sisters and classmates are very good , Happy every day , Some are studying hard , Slowly groping , Make friends seriously . Although most of the time is busy , But because there are a group of lovely people around and become happy and full .

Although I don't know what will happen in the future , But will always be enthusiastic , Strive to move forward in the exploration .

To know and then to know , Be sure to be quiet , Be quiet and then be safe , You can worry about it , Worry before you get . Everything has its roots and ends , There is an end to it . know what should precede and what should follow , It's a short cut .

Please give me more advice , Come on !

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