MNIST Handwritten Digit Recognition using a baseline CNN model MNIST dataset consists of handwritten digit images in black and white. The project aims at creating a basic CNN model and train them to accurately classify the digits. The baseline model obtains an accuracy of 98.6% on the MNIST dataset.
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Made with ❤️ by Vivek Padayattil