CNN is a relatively new field if you have done a little bit of deep learning, so you may think you know it, but it is harder to respond flexibly than you think because you don't know the principles and use it. Whenever the company needs it, I search for github or quickly combine the functions I need at the time without knowing the principles. While doing it while doing other work, I kept putting off studying tensorflow2.4, keras, and kaggle, thinking that I would study them someday. However, I remember successfully applying object detection to robot movement in a project I took the last lecture, and being recognized as an expert(?) at the company, so I am taking the class to organize CNN again and look into it in depth. The class time is not short, but it is not bad because the source code is explained in detail, so I think it would be good to quickly look through it and mark it separately and listen to the parts I need in more detail later. --------------------------------------------------------- I am adding this to the review I left before. I did other work at the company, and then the computer vision department was created again, so I listened to it from the beginning again to review it. When I listened to it again, I realized that I had a wider range of understanding of the parts that I had rushed through before. This is not a lecture that you can listen to once and finish. I highly recommend it again.