The website for Cycle GANs project @ UIUC

A Handwritten Digit Recognizer on the Web. Model trained locally on MNIST with ANN built from scratch.

A web application which identifies the digits drawn by the user on a canvas provided in the app.

NUMI AI is an intuitive web application that recognizes hand-drawn single-digit numbers in real-time. Using a powerful Convolutional Neural Network (CNN), NUMI AI provides accurate predictions.

MNIST tutorial in browser using Tensorflow.js

Multiple Python Keras models, trained on the MNIST dataset, served on a interactive webpage through the use of Tensorflow JS for loading and getting predictions from the model and p5.js for canvas operations.

a handwritten digit detection system powered by tensorflow

An implementation showcasing the deployment of machine learning model onto the flask server with live demo deployed on AWS Lambda.

Mnist dataset playground tensorflowjs

machine learning front-end avec TensorFlowJs

This project is a web application that uses TensorFlow.js to train a convolutional neural network on the MNIST dataset to recognize handwritten digits, and allows users to draw their own digits on a canvas and have the model predict the number. It is compatible with both desktop and mobile devices.

Coursework for an ai course around the perceptron at Cologne University of Applied Sciences

Image classifier written in javascript using the MNIST database of handwritten digits

My first Neural network model inside a web application.