{"id":20165337,"url":"https://github.com/ayodimeji1/ai_classification-nn","last_synced_at":"2026-05-02T17:33:45.411Z","repository":{"id":259966718,"uuid":"879936934","full_name":"Ayodimeji1/AI_Classification-NN","owner":"Ayodimeji1","description":null,"archived":false,"fork":false,"pushed_at":"2024-11-04T04:50:39.000Z","size":930,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-03T03:25:39.377Z","etag":null,"topics":["data-analysis","feature-engineering","jupyter-notebook","keras","machine-learning","neural-networks","python","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/Ayodimeji1.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,"publiccode":null,"codemeta":null}},"created_at":"2024-10-28T20:17:00.000Z","updated_at":"2024-11-04T04:51:03.000Z","dependencies_parsed_at":null,"dependency_job_id":"5e7929a5-c7dd-4add-994b-00ab0e7e50c1","html_url":"https://github.com/Ayodimeji1/AI_Classification-NN","commit_stats":null,"previous_names":["ayodimeji1/ml_classification-nn","ayodimeji1/ai_classification-nn"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/Ayodimeji1/AI_Classification-NN","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Ayodimeji1%2FAI_Classification-NN","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Ayodimeji1%2FAI_Classification-NN/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Ayodimeji1%2FAI_Classification-NN/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Ayodimeji1%2FAI_Classification-NN/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Ayodimeji1","download_url":"https://codeload.github.com/Ayodimeji1/AI_Classification-NN/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Ayodimeji1%2FAI_Classification-NN/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":278277859,"owners_count":25960428,"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","status":"online","status_checked_at":"2025-10-04T02:00:05.491Z","response_time":63,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"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":["data-analysis","feature-engineering","jupyter-notebook","keras","machine-learning","neural-networks","python","tensorflow"],"created_at":"2024-11-14T00:37:29.133Z","updated_at":"2025-10-04T06:37:04.656Z","avatar_url":"https://github.com/Ayodimeji1.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"\n# ML Classification - Neural Networks Project\n\n## Overview\n\nThis project focuses on implementing classification tasks using neural networks. It is designed to provide an in-depth understanding of how to build, train, and evaluate neural network models for classification problems. The project is presented in a Jupyter Notebook format, which makes it interactive and suitable for demonstration and educational purposes.\n\n## Table of Contents\n\n- [Features](#features)\n- [Project Structure](#project-structure)\n- [Installation](#installation)\n- [Usage](#usage)\n- [Dependencies](#dependencies)\n- [Configuration](#configuration)\n- [Project Details](#project-details)\n- [License](#license)\n\n## Features\n\n- **Neural Network Architecture**: Implementation of a neural network for classification.\n- **Data Preprocessing**: Methods to clean and prepare data for training.\n- **Training and Evaluation**: Includes training the model, validation, and performance metrics.\n- **Interactive Notebook**: Step-by-step code explanations and outputs.\n- **Visualization**: Visualizes training metrics and model performance.\n\n## Project Structure\n\n```\nML_Classification-NN-main/\n│\n├── Task_3_Classification_Neural_Networks.ipynb  # Jupyter Notebook with neural network implementation\n└── README.md                                    # Project documentation\n```\n\n## Installation\n\n### Prerequisites\n- **Python 3.8+**\n- **Jupyter Notebook** or **Jupyter Lab**\n\n### Setup\n\n1. **Clone the repository**:\n   ```\n   git clone https://github.com/Ayodimeji1/ML_Classification-NN.git\n   cd ML_Classification-NN-main\n   ```\n\n3. **Install the required packages**:\n   ```\n   pip install numpy pandas matplotlib scikit-learn tensorflow\n   ```\n\n## Usage\n\n1. **Launch Jupyter Notebook**:\n   ```\n   jupyter notebook\n   ```\n\n2. **Open `Classification_Neural_Networks.ipynb`** in the Jupyter interface and execute the cells step-by-step to explore the code and outputs.\n\n## Dependencies\n\n- **NumPy**: For numerical operations\n- **Pandas**: For data manipulation\n- **Matplotlib/Seaborn**: For visualizations\n- **Scikit-learn**: For data splitting and evaluation\n- **TensorFlow/Keras or PyTorch**: For building and training the neural network\n- **Jupyter Notebook**: For interactive coding environment\n\n## Configuration\n\n- **Data File**: Ensure any dataset required is available and properly referenced in the notebook.\n\n## Project Details\n\nThe notebook walks through the process of:\n\n- **Data Loading and Preprocessing**: Cleaning and preparing the dataset.\n- **Model Building**: Creating a neural network architecture tailored for classification.\n- **Training**: Configuring training loops, defining loss functions, and using optimizers.\n- **Evaluation**: Assessing model performance using metrics such as accuracy, precision, and recall.\n- **Visualization**: Plotting learning curves and evaluation metrics for better insight.\n\n## License\n\nThis project is licensed under the MIT License. \n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fayodimeji1%2Fai_classification-nn","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fayodimeji1%2Fai_classification-nn","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fayodimeji1%2Fai_classification-nn/lists"}