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Using Multi Layer Perceptron to build the model. Classifies the handwritten digits of the MNIST database with around 98% accuracy.

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Handwritten Digit Classification Using MLP.ipynb

Handwritten Digit Classification Using MLP.ipynb

 
 

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README.md

 
 

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Handwritten-Digit-MLP-Classification

Using the MNIST database. It is a collection of 70000 handwritten digits split into training and test set of 60000 and 10000 images respectively.

The model is built using Multi Layer Perceptron (MLP).

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Using Multi Layer Perceptron to build the model. Classifies the handwritten digits of the MNIST database with around 98% accuracy.

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pytorch handwritten-digits mnist-database

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