Get and solve the handwriting dataset from MNIST
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Updated
Oct 1, 2017 - Python
Get and solve the handwriting dataset from MNIST
Small python 3 tool to load the MNIST dataset from keras and save each entry to a *.png file
This is a simple Django REST framework application for a prediction endpoint on the MNIST trained CapsNet model
MNIST tutorial in browser using Tensorflow.js
All assignments of Statistical Machine Learning Course
Implementation of LeNet 5 using PyTorch for the MNIST dataset.
🤖 DigitMe is a hand written digit recognizer in the web written in Python and VueJS.
Digit Recognizer is a CNN based model which recognizes images of handwritten digits using keras.
Implementation of DCGAN model to train a neural network on mnist dataset and generate fake handwritten digits close enough to the real images from the dataset.
A Deep Neural Network Playground
intro to ML/AI by solving the MNIST dataset using different classification methods
Handwritten Digit Recognizer written in python using tkinter(for gui), keras(models, datasets etc.), PIL(Image grabbing & filtering) and Tensorflow modules.
MNiST Classification Using Tensorflow GPU
A study of the use of the Tensorflow GradientTape class for differentiation and custom gradient generation along with its use to implement a Deep-Convolutional Generative Adversarial Network (GAN) to generate images of hand-written digits.
Implementation of a Quantized Neural Network with low bitwidth of weights, activations and gradients.
This is basic image classification code for mnist dataset.(hand written digits' data)
Neural network trained to detect handwritten numbers.
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