Learning route introduction
written in front
Once the video course on the basics of fault diagnosis based on signal processing in the previous stage was launched, it has been well received by many students. I am delighted but also feel quite pressured. I have been thinking about how to really help everyone from the perspective of scientific research. My student audience is also very wide, most of them are masters, doctors and a small number of postdoctoral practitioners, many of whom are top 985 students. After getting along, I summed up some commonalities of everyone: 1. I couldn’t grasp the key points at the beginning, and it was uncomfortable to read the literature in a cloud of fog; 2. The coding ability is relatively weak, even if I have a good idea in my mind, I can’t help it Write out the program; 3. Doctors or masters want to publish high-level journals, but can't find innovative points; 4. I am confused about future work and employment planning. In fact, these problems are indeed problems that everyone in this field will encounter. You don’t need to be overly anxious. You just need to do what you need to do at each stage step by step, and the boat will naturally go straight to the bridge. At the same time, I will also design practical courses that are more in line with the "study situation" to address these pain points of everyone. I have been asking myself: If it is taught according to the script, what is the difference from those "deep learning courses" on station B?
The My Diagnosis Home student group is called a holy place for learning by students. Here, everyone exchanges scientific research issues, shares learning materials and daily life of graduate school, complains about topics or tutors, shares employment information, and so on. Seeing everyone gradually adapting to scientific research life from Xiaobai, my heart is both gratified and moved. Over the years, I have successively taught more than one hundred students. This number is not too much, and it is not an exaggeration.
I have persisted until now. It is purely a hobby. From the very beginning of repulsion to gradual acceptance, I have experienced the ups and downs that every student is going through, especially seeing that the algorithm in my previous laboratory can truly Landing in the product, this feeling is really good.
Learning Outline
In terms of machine learning, the basic introductory course series intends to only select SVM and artificial neural network to explain. The course format is in the form of video, which is constantly updated, combined with hand-in-hand analysis of source code. If necessary, a paper will be explained as a case analysis. In the part of deep learning, we will mainly explain CNN, DNN and RNN. The language choice of this series is considered to be Python, and Matlab will also provide corresponding code materials.
Diagnosis House Introduction
This group feels that everyone is very active every day. There are students of different levels in it, and there are even third-year PhD students. I think it is very good to communicate and share knowledge in the group every day.
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