A simple, easy to use MNIST loader written in Python 3
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Updated
May 13, 2020 - Python
A simple, easy to use MNIST loader written in Python 3
Practice models and visualizations using a modified set of digit images from the MNIST database.
Artificial neural networks processed with Tensorflow
Using Multi Layer Perceptron to build the model. Classifies the handwritten digits of the MNIST database with around 98% accuracy.
A 3-layer neural network to differentiate handwritten digits in MNIST database
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Python module to download and extract the MNIST database for training and testing deep learning neural networks in computer vision.
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mnist dataset for hand written digit recognition
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An application that uses tensorFlow to recognize handwritten numerical digits from MNIST database of handwritten digits.
A naive sklearn-driven script to learn the best parameters for the MNIST database
A simple API for C language created to work easier with MNIST data files.
A simple implementation of a Restricted Boltzmann Machine, able to perfrom a supervised classification task on the MNIST database of handwritten digits, coded for prof. Bortolozzi course Biological Physics @unipd
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