A Flask web app for handwritten digit recognition using machine learning

A Hand Written Digit Recognition app trained on the MNIST dataset of Keras using the CNN model. skills used are Tensorflow, HTML,CSS,javascript.

✏️ An AI-driven web app for handwritten digit recognition using the MNIST dataset. It leverages TensorFlow for deep learning model training and Gradio to create an intuitive, interactive UI. Users can draw digits and receive instant predictions, showcasing practical AI deployment and real-time inference capabilities.

A Flask web app for handwritten digit recognition using machine learning

A simple digit recognition web app built as my first project in the field of Machine Learning.

Flask web app for realtime handwritten digit recognition using CNN model (MNIST dataset).

It recognizes the digit written on the editor provided in the interface and displays the result which is predicted .

Digit recognition Flask Web app using TensorFlow

A handwritten digit recognition web app using Convolutional Neural Networks. Built with Keras and Tensorflow.js

Digit recognition web app made with TensorflowJS

A sample web app in node.js for hosting a CNTK model for hand written digits recognition

Production-ready deep learning model for handwritten digit recognition using optimized CNN architecture. Features interactive web app, comprehensive training pipeline, and multiple deployment options. Achieves 99.65% accuracy on MNIST dataset with advanced data augmentation and regularization techniques.

CNN EMNIST Visualization is a deep learning project that trains CNN models on MNIST digits and EMNIST letters. It includes a Streamlit web app for drawing characters and viewing real-time predictions, making it ideal for learning and demonstrating handwritten recognition using CNNs.

Handwritten Digit Recognition WebApp using Flask and TensorFlow

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A simple digit recognition web app using an artificial neural network built from scratch

This project is a web-based handwritten digit recognition app using a CNN model built with Keras and TensorFlow, deployed with Flask. Users draw digits in the browser, which the model classifies in real-time. With a high accuracy , it offers an interactive, accurate interface for digit recognition.

AI-powered handwritten digit recognition web app using Flask & CNN.

A web app for digit recognition using a custom neural network trained on MNIST. Draw digits, get predictions with confidence scores. Built with Flask and NumPy

This project is a handwritten digit recognition web app built using Streamlit and a pre-trained deep learning model (HandWrittenDigit.pkl). The app allows users to upload an image of a digit (0-9) and predicts the number using a CNN model trained on the MNIST dataset.

A web application that allows you to sketch a number and get the predicted class.

A Handwritten Digit Recognition Web App

This is a React App that uses a Convolutional Neural Network-based model (trained on MNIST dataset) to recognize the digit drawn by the user using their mouse.

A Hand Written Digit Recognition app trained on the MNIST dataset of Keras using the CNN model. skills used are Tensorflow, HTML,CSS,javascript.

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End-to-end MNIST digit recognition web app (CNN)

Demo for a simple handwritten digit recognition web app

Digit Recognition web app with Spring Boot and React.

Deep learning digit recognition web application with flask server.

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