Распознавание номеров домов (SVHN) для робота-курьера: чистый PyTorch/Lightning конвейер, воспроизводимые эксперименты, Docker, CI, Streamlit-демо, модельная карточка, тесты.

A complete, straightforward digit classification project built with PyTorch, featuring CNN-based training, evaluation metrics, confusion matrix visualization, and XAI using Grad-CAM.

Deep learning image classification projects using TensorFlow & Keras — includes CIFAR-10, MNIST digit recognition, and bone fracture detection.

Handwritten digit recognition from a single image using a neural network

A Drag&Drop Sudoku Solver

classify handwritten digits (0-9)

5x5 digits recognize by neural network & Training data

A simple neuron network app made for guessing hand-written digits.

Convolutional neural network model for handwritten digit classification, with dataset generator, and drawable input for new digits to test the models.

experimenting with ai

CNN-based Text Recognition for Automatic License Plate Recognition (ALPR).

Digit recognition with tensorflow

Handwritten digit recognizer AI.

Simple perceptron to recognize handwritten digits and application to demonstrate this ability

Real-time Handwritten Digit Recognition using Python and OpenCV.

The handwritten digit recognition is the ability of computers to recognize human handwritten digits. It is a hard task for the machine because handwritten digits are not perfect and can be made with many different classifier model

This document explores the use of Principal Component Analysis (PCA) in a machine learning context, specifically for image classification using a dataset of numerical representations of digits. The dataset is loaded using sci-kit-learn's load_digits function, and initial exploration is conducted to understand its structure.

Simple Tensorflow model for recognizing digits, built over the MIST dataset

An implementation of a Multilayer Perceptron (MLP) neural network from scratch to recognize handwritten digits.

Digits detection with YOLOv8 detection model and ONNX pre/post processing