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I have worked and studied data for 2 years now so I think i know the basics of Cnn, backpropagation, feature extraction, etc. I took the jose portilla course on udemy for computer vision with opencv and i read a book name "deep learning for vision systems" by elgendy. I learned about alexnet, lenet, googlenet, resnet, vgg, etc in the book and tried them out in keras. I want to learn how to get a good hold on pytorch to load the models in pytorch, load the data, preprocess the data and get the predictions. I searched online but couldn't find any resources. I want to be able to do something like this with the main yolov7 branch and the u7 branch where I have trained the model on my custom dataset.