Naive Implementation of PyTorch framework to solve the MNIST-Digit_Recognition Problem
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Updated
Sep 10, 2019 - Python
Naive Implementation of PyTorch framework to solve the MNIST-Digit_Recognition Problem
NumPy-based feed-forward neural network
An MNIST dataset classifier implemented from scratch in NumPy.
MNIST classifier with a graphical user interface and a canvas for drawing the digits, doing classifying in real time
MNIST Classification with Convolutional Neural Networks
Performing Handwritten Digit Classification on MNIST dataset using PyTorch-Lightning
This repository includes a study that aims to apply classification on well-known MNIST dataset. Detailed info in ReadMe
MNIST Digits Classification with numpy only
Study of leNet implementation in Python3.6 with Keras+Tensorflow backend.
Neural networks for digit classification trained using the MNIST database
Epoch introduction to neural networks intersession, SY2021
Played with Tensorspace a library for Neural network 3D visualization, building interactive and intuitive models in browsers, supports pre-trained deep learning models from TensorFlow, Keras, TensorFlow.js
Digit Recognizer - Convolutional Neural Network trained with mnist model using matplotlib - Duke University Class
"Quantum-Inspired MNIST" achieved 72% accuracy using nothing but means, addition, and subtraction. This experiment adds standard deviations.
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