A simple JavaScript neural network framework.
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Updated
Nov 20, 2019 - JavaScript
A simple JavaScript neural network framework.
Vanilla neural network implemented in all major languages
A deep learning model to classify the Arabic letters and digits easily.
Neural network library written in C and Javascript
A collection of some cool deep learning projects in python
code recognition persian handwritten
A Neural Network implemented from scratch as per http://neuralnetworksanddeeplearning.com/ in Rust. This is then trained on MNIST. This is also used in Rust-NN-Web project to compile to WASM and recognize digits.
Super Resolution's the images by 3x using CNN
This program uses ML to recognize a handwritten number written anywhere on a blank paper with preferable black ink. Please make sure that the image is of apt resolution.
Recognize Handwritten Digits(persian/english) with Neural Networks
This uses the Rust-NN, compiled to WASM, to recognize digits on frontend, without sending the data to backend.
Building a deep learning model for recognizing handwritten numbers.
Neural network that reads handwritten numbers.
I have used a Multi-Layer Perceptron (MLP) neural network to classify handwritten Persian digits dataset. I have plotted the error curve during the training phase. It has been explained what maximum accuracy is achieved. Additionally, I have examined the accuracy of recognizing different digits.
recognize mouse-written numbers using KNN, Neural Network, and Convolutional Neural Network models
A small example using WPF and ML.Net for training and recognize handwritten numbers using a stylus/pen.
Using ML to create a model which would predict/recognize the english alphabet from our own dataset.
This repository contains a notebook to take you through step by step guide on recognizing handwritten digits using a Multi-Layer-Perceptron(MLP)
Classifying handwritten digits (MNIST) using multi-layer perceptron in PyTorch.
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