matin-ghorbani/MNIST-RNN
Inference RNN, GRU and LSTM on Mnist dataset
This project helps developers and researchers evaluate different recurrent neural network (RNN) architectures for digit recognition. It takes handwritten digit images (like those from the MNIST dataset) and outputs a classification of the digit, along with the accuracy of the model. Machine learning practitioners focused on sequence data and image classification would find this useful for benchmarking.
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Use this if you are a machine learning developer or researcher needing to quickly compare the performance of RNN, GRU, and LSTM models on a standard handwritten digit classification task.
Not ideal if you are looking for a ready-to-use application for digit recognition or if you are not comfortable with Python and machine learning development.
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Language
Python
License
MIT
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Last pushed
Jul 21, 2024
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