How to download data in Pytorch and define DataLoader for MNIST Image Classification

This video is the third video of a 5-video playlist in writing an image classifier from scratch in Pytorch. In this video, you would see how easily one can define HYPERPARAMETRS, MODEL, DEVICE, OPTIMIZER and LOSS FUNCTION. You would also learn how to download MNIST data and wrap a DATALOADER around the downloaded dataset. You will learn all of this in LESS THAN 10 MINUTES!!!

IF YOU HAVE NO DEEP LEARNING/PYTORCH EXPERIENCE and want to learn them by actually writing an image classifier, this video and the rest of the videos in THIS PLAYLIST ARE BUILT FOR YOU. Here we write all the codes from scratch in order to classify the images of handwritten numbers (MNIST dataset). THE RATIONALE BEHIND EVERY LINE OF CODE IS EXPLAINED HERE, SO YOU WON'T MISS THE BACKGROUND WHAT SO EVER!!!

#DeepLearning #Computervision #MNIST #ImageClassification #Pytorch #torch #torchvision #neuralnetwork #DataLoader #Training #Testing

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