Image source: https://metrology.news/ai-for-smarter-factories-the-world-of-industrial-artificial-intelligence/
In order to help everyone do a good job in industrial software and use artificial intelligence to solve practical problems in the industrial field, I opened two video series on station B, one is "Let's read open source industrial software together", and the other is "Industrial Intelligence Theory Cases and Practices" .
1 Let's read open source industrial software together
I would like to read the following open source industrial software code with you
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Siemens open IoT operating system MindSphere , MindSphere code repository
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The time series database TDEngine belongs to the basic software and has many applications in industrial manufacturing. Product official website , time series database TDEngine code base
The activity is in the form of flipped classroom.
1. Record and play the code reading video: I will record the code reading video
2. Online Q&A: everyone discusses the problems encountered in the process of reading the code
3. Online summary: everyone chats and makes industrial software on CSDN "The community publishes the experience and gains of reading code.
1. How to read open source code?
The first topic: How to read open source software?
1 Why read code? Why,
2 Which codes to read? What,
3 Where can I find the code? Where,
4 How to read the code? how
4.1 Basics of reading code
4.2 Methods of reading large projects
reference resources
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7 Ways to Improve Your Code Reading Skills：https://dzone.com/articles/7-ways-to-improve-your-code-reading-skill
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Tips For Reading Code：http://wiki.c2.com/?TipsForReadingCode
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Java Coding Samples：https://www.cs.utexas.edu/~scottm/cs307/codingSamples.htm
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Vertx toolkit for building reactive applications on the JVM https://vertx.io/
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General Artificial Intelligence System NARS https://github.com/opennars/opennars
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Code Reading: The Open Source Perspective https://www.spinellis.gr/codereading/
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The NetBSD Project https://www.netbsd.org/
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https://github.com/eraft-io/eraft
2 Case Practice of Industrial Intelligence Theory
I have mentioned the content related to industrial intelligence in the following article.
【Learning resources】Let's do industrial intelligence together
Now you can see 53 videos related to industrial intelligence that I released on Station B
Industrial intelligence theory case practice video album
The supporting content of the video is on github
Industrial artificial intelligence course sharing
The content of the topic is as follows, and I will continue to add new videos based on the current development of theory and technology, especially practical examples to help you understand the specific details that need to be paid attention to in real applications.
This series of videos uses industrial situations as modules to learn basic theoretical knowledge, key technologies, and practical cases. Through cases, from the three aspects of problem description, data resources and solutions, practice the method of using artificial intelligence theory and technology to solve industrial problems, including fault pre-diagnosis and equipment health management PHM, intelligent quality inspection based on computer vision, time-series data-based Production and operation optimization of analysis technology, production scheduling, production quality analysis method, production fault defect inspection and location, application of intensive learning in industry, fault warning knowledge base of industrial knowledge management. There is no shortage of theoretical techniques, case studies, and practical exercises. There are many experimental examples in the video where I use 4 GPU V100S for training. :)
For the entire series, check out this video.
0. Introduction to Industrial Artificial Intelligence Practical Courses
Welcome to study. For the basics needed to learn this course, please check the preparations before learning and the solutions to common problems in Anaconda
Machine Learning Practical Skills
The learning process is to watch the video first, and then complete the exercises. The details of the exercises are in the actual combat exercises of industrial intelligence . If you have theoretical and practical questions, please leave a message in each episode of the video, or you can publish them at https://github.com/bettermorn/IAICourse/issues Questions, I'll try to answer them as best I can.
If you need to know other content, you can also view the industrial artificial intelligence course sharing
Welcome everyone to leave a message and communicate with me how to do a good job in industrial software and industrial intelligence. I hope that we can all start from the problem, make contributions within our capacity to the field of industrial manufacturing, and make excellent results.