{"id":22051626,"url":"https://github.com/ehvenga/mnist.handwritten.digit.recognition-tensorflow","last_synced_at":"2026-05-09T01:14:00.296Z","repository":{"id":234559849,"uuid":"788874845","full_name":"ehvenga/mnist.handwritten.digit.recognition-tensorflow","owner":"ehvenga","description":"This Jupyter Notebook demonstrates a TensorFlow model for recognizing handwritten digits using the MNIST dataset, focusing on model construction, training, and accuracy evaluation.","archived":false,"fork":false,"pushed_at":"2024-04-19T19:42:23.000Z","size":329,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-20T21:17:47.890Z","etag":null,"topics":["computer-vision","convolutional-neural-networks","handwritten-digit-recognition","machine-learning","mnist-classification","tensorflow"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/ehvenga.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null}},"created_at":"2024-04-19T08:57:54.000Z","updated_at":"2024-04-19T19:53:10.000Z","dependencies_parsed_at":"2024-04-19T20:57:10.184Z","dependency_job_id":null,"html_url":"https://github.com/ehvenga/mnist.handwritten.digit.recognition-tensorflow","commit_stats":null,"previous_names":["ehvenga/mnist-handwritten-recognition"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ehvenga%2Fmnist.handwritten.digit.recognition-tensorflow","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ehvenga%2Fmnist.handwritten.digit.recognition-tensorflow/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ehvenga%2Fmnist.handwritten.digit.recognition-tensorflow/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ehvenga%2Fmnist.handwritten.digit.recognition-tensorflow/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ehvenga","download_url":"https://codeload.github.com/ehvenga/mnist.handwritten.digit.recognition-tensorflow/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":245121697,"owners_count":20564163,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["computer-vision","convolutional-neural-networks","handwritten-digit-recognition","machine-learning","mnist-classification","tensorflow"],"created_at":"2024-11-30T15:09:58.980Z","updated_at":"2026-05-09T01:13:55.263Z","avatar_url":"https://github.com/ehvenga.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# MNIST Digit Recognition using TensorFlow\n\n## Overview\n\nThis repository contains a Jupyter Notebook that demonstrates the use of TensorFlow to recognize handwritten digits from the MNIST dataset. The project utilizes a convolutional neural network (CNN) for high accuracy in digit classification.\n\n## Prerequisites\n\n- Python 3.x\n- TensorFlow 2.x\n- NumPy\n- Matplotlib (for visualization)\n\n## Installation\n\nTo get started with this project, clone the repository to your local machine:\n\n```bash\ngit clone https://github.com/your-username/mnist-digit-recognition.\n\n\njupyter notebook MNIST_Digit_Recognition.ipynb\n```\n\n## Dataset\n\nThe MNIST dataset comprises 70,000 grayscale images of handwritten digits (0-9), each of size 28x28 pixels. The dataset is split into 60,000 training images and 10,000 testing images.\n\n## Model\n\nThe notebook details the CNN architecture used for digit classification, including layers, activation functions, and compilation strategy.\n\n## Evaluation\n\nEvaluation metrics are provided within the notebook to assess the accuracy and effectiveness of the trained model on test data.\n\n## Contributing\n\nContributions to this project are welcome. Please fork the repository and submit pull requests to enhance the functionality or performance of the model.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fehvenga%2Fmnist.handwritten.digit.recognition-tensorflow","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fehvenga%2Fmnist.handwritten.digit.recognition-tensorflow","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fehvenga%2Fmnist.handwritten.digit.recognition-tensorflow/lists"}