HELLO GUYS, IN THIS BLOG POST I WANT TO SHOW THE BASIC INTRO TO IDENTIFICATION OF HANDWRITTEN DIGITS USING PYTORCH MNIST DATA. MNIST DATA IS THE COLLECTION OF HANDWRITTEN DIGITS. MNIST CONTAINS 70,000 HANDWRITTEN DIGITS, 60,000 FOR TRAINING AND REMAINING 10,000 ARE FOR TESTING. THE IMAGES ARE GRAYSCALE AND 28x28 PIXELS. WE CAN DOWNLOAD THE DATASET USING THE CODE BELOW. Here, the parameters batch_size is kept to 64 so that the training images are grouped into 64 each and shuffle is kept to TRUE, such that each time we run the code it shuffles the data and returns an iterable with new groups of batch_size. As the trainloader is iterable, we are iterating through it and collecting the first batch of images and it's corresponding labels into images and labels respectively. Now, run the above code and see the output. you will see something like this. torch.Size([64, 1, 28, 28]) torch.Size([64]) It shows that there are 64 images with grayscale an...
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