{"id":29061690,"url":"https://github.com/moustafamohamed01/dl-projects","last_synced_at":"2026-04-12T05:32:01.825Z","repository":{"id":300638836,"uuid":"989402051","full_name":"MoustafaMohamed01/DL-Projects","owner":"MoustafaMohamed01","description":"A curated collection of deep learning projects showcasing applications of neural networks, CNNs, RNNs, and more, built with TensorFlow, PyTorch, and Python.","archived":false,"fork":false,"pushed_at":"2025-06-22T20:48:22.000Z","size":994,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2025-06-22T21:18:09.715Z","etag":null,"topics":["ann","cnn","deep-learning","keras","python","pytorch","rnn","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/MoustafaMohamed01.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,"zenodo":null}},"created_at":"2025-05-24T03:04:43.000Z","updated_at":"2025-06-22T20:48:25.000Z","dependencies_parsed_at":"2025-06-22T21:18:12.335Z","dependency_job_id":"cde5cd11-8624-4bed-bffc-3c60849ddb06","html_url":"https://github.com/MoustafaMohamed01/DL-Projects","commit_stats":null,"previous_names":["moustafamohamed01/dl-projects"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/MoustafaMohamed01/DL-Projects","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MoustafaMohamed01%2FDL-Projects","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MoustafaMohamed01%2FDL-Projects/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MoustafaMohamed01%2FDL-Projects/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MoustafaMohamed01%2FDL-Projects/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/MoustafaMohamed01","download_url":"https://codeload.github.com/MoustafaMohamed01/DL-Projects/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MoustafaMohamed01%2FDL-Projects/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":262219800,"owners_count":23276888,"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":["ann","cnn","deep-learning","keras","python","pytorch","rnn","tensorflow"],"created_at":"2025-06-27T08:04:00.364Z","updated_at":"2025-12-30T22:22:41.799Z","avatar_url":"https://github.com/MoustafaMohamed01.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Deep Learning Projects Portfolio\n\nWelcome to my portfolio of deep learning projects, A curated collection of deep learning projects implemented using **TensorFlow**, **Keras**, and **PyTorch**. This repository demonstrates practical applications of neural networks in domains such as image classification, generative modeling, and medical diagnostics, emphasizing clean code, reproducibility, and performance evaluation.\n\n---\n\n## Repository Structure\n\nEach subfolder within this repository contains an independent deep learning project, complete with source code, dataset details, training instructions, and results visualization.\n\n| Project                                                                                             | Framework        | Domain                | Key Topics                              |\n| --------------------------------------------------------------------------------------------------- | ---------------- | --------------------- | --------------------------------------- |\n| [Fruit \u0026 Vegetable Image Classification](#1-fruit--vegetable-image-classification)                  | TensorFlow/Keras | Image Classification  | CNNs, Image Processing                  |\n| [Breast Cancer Prediction using Neural Networks](#2-breast-cancer-prediction-using-neural-networks) | PyTorch          | Binary Classification | Feedforward Neural Networks, Medical AI |\n| [Fashion MNIST Image Classification](#3-fashion-mnist-image-classification)                         | TensorFlow/Keras | Image Classification  | CNNs, Regularization                    |\n| [Face Mask Detection](#4-face-mask-detection)                                                       | TensorFlow/Keras | Binary Classification | Real-Time Detection, CNN, OpenCV        |\n| [MNIST GAN – Digit Generation](#5-mnist-gan--digit-generation)                                      | TensorFlow       | Generative Modeling   | GANs, Image Synthesis                   |\n| [Anime Face Generator (DCGAN)](#6-anime-face-generator-dcgan)                                       | TensorFlow       | Generative Modeling   | DCGAN, Image Generation, Anime Faces    |\n\n---\n\n## 1. Fruit \u0026 Vegetable Image Classification\n\nA convolutional neural network (CNN) designed to classify images of fruits and vegetables.\n\n**Technologies:** TensorFlow, Keras, Python  \n**Dataset:** [Kaggle - Fruit and Vegetable Image Recognition](https://www.kaggle.com/datasets/kritikseth/fruit-and-vegetable-image-recognition)\n\n### Highlights\n\n* Data preprocessing and augmentation  \n* CNN architecture with Dropout and MaxPooling  \n* Real-time prediction support with confidence scores  \n* Training and validation performance visualization\n\n📁 Folder: [Fruits-and-Vegetables-Image-Recognition-Dataset](./Fruits-and-Vegetables-Image-Recognition-Dataset)\n\n---\n\n## 2. Breast Cancer Prediction using Neural Networks\n\nA binary classification model developed using PyTorch to predict tumor malignancy from the Breast Cancer Wisconsin dataset.\n\n**Technologies:** PyTorch, Scikit-learn, Matplotlib  \n**Dataset:** [sklearn.datasets.load_breast_cancer](https://scikit-learn.org/stable/modules/generated/sklearn.datasets.load_breast_cancer.html)\n\n### Highlights\n\n* FFNN architecture  \n* Binary cross-entropy loss with Adam optimizer  \n* Training curves and evaluation metrics  \n* Available in Jupyter and standalone script formats\n\n📁 Folder: [breast-cancer-prediction](./breast-cancer-prediction)\n\n---\n\n## 3. Fashion MNIST Image Classification\n\nA CNN-based image classifier trained on Fashion MNIST dataset, classifying clothing items into 10 categories.\n\n**Technologies:** TensorFlow, Keras  \n**Dataset:** [`tensorflow.keras.datasets.fashion_mnist`](https://www.tensorflow.org/datasets/catalog/fashion_mnist)\n\n### Highlights\n\n* Batch Normalization and Dropout layers  \n* EarlyStopping and ModelCheckpoint callbacks  \n* Accuracy up to 91–93% with tuning  \n* Stylish metric visualizations\n\n📁 Folder: [Fashion-MNIST-Image-Classification](./Fashion-MNIST-Image-Classification)\n\n---\n\n## 4. Face Mask Detection\n\nA real-time CNN classifier that detects whether a person is wearing a face mask or not.\n\n**Technologies:** TensorFlow, Keras, OpenCV, Python  \n**Dataset:** [Kaggle - Face Mask Dataset](https://www.kaggle.com/datasets/omkargurav/face-mask-dataset)\n\n### Highlights\n\n* Binary classification: With Mask 😷 vs Without Mask 😐  \n* Data augmentation and preprocessing  \n* Real-time prediction from user-provided images  \n* Model saved and reloadable (`.h5`)  \n* GPU support and training visualizations\n\n📁 Folder: [face-mask-detection](./face-mask-detection)\n\n---\n\n## 5. MNIST GAN – Digit Generation\n\nA Generative Adversarial Network (GAN) that synthesizes realistic handwritten digits from the MNIST dataset.\n\n**Technologies:** TensorFlow, Python  \n**Dataset:** [`tensorflow.keras.datasets.mnist`](https://www.tensorflow.org/datasets/catalog/mnist)\n\n### Highlights\n\n* Fully functional GAN (Generator + Discriminator)  \n* Saves generated digit images every epoch  \n* GAN-stabilization tricks: label smoothing, custom beta values  \n* Available in both `.py` and `.ipynb` formats\n\n📁 Folder: [mnist-gan](./mnist-gan)\n\n---\n\n## 6. Anime Face Generator (DCGAN)\n\nA Deep Convolutional GAN (DCGAN) trained on anime character faces to generate high-quality synthetic images.\n\n**Technologies:** TensorFlow, Keras, Python  \n**Dataset:** [Kaggle - Anime Face Dataset](https://www.kaggle.com/splcher/animefacedataset)\n\n### Highlights\n\n* DCGAN architecture with Conv2DTranspose and LeakyReLU  \n* Trained on 64×64 anime face images  \n* Outputs generated image grids every 50 epochs  \n* Modular code: available in both notebook and script formats  \n* Excellent visual results for anime face synthesis\n\n📁 Folder: [anime-gan](./anime-gan)\n\n---\n\n## Installation \u0026 Setup\n\n1. **Clone the Repository**\n\n```bash\ngit clone https://github.com/MoustafaMohamed01/DL-Projects.git\ncd DL-Projects\n````\n\n2. **Install Dependencies**\n   Each project includes a `requirements.txt`. To install dependencies:\n\n```bash\npip install -r requirements.txt\n```\n\n3. **Run Projects**\n   Navigate to the relevant folder and follow its README to train or run inference.\n\n---\n\n## Contributing\n\nContributions are welcome! If you’d like to improve a project or add a new one:\n\n1. Fork the repository\n2. Create a new branch\n3. Submit a pull request\n\nIdeas, feedback, and improvements are always appreciated.\n\n---\n\n## Connect With Me\n\n* **LinkedIn:** [Moustafa Mohamed](https://www.linkedin.com/in/moustafamohamed01/)\n* **GitHub:** [MoustafaMohamed01](https://github.com/MoustafaMohamed01)\n* **Kaggle:** [moustafamohamed01](https://www.kaggle.com/moustafamohamed01)\n* **Portfolio:** [moustafamohamed.netlify.app](https://moustafamohamed.netlify.app/)\n\n---\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmoustafamohamed01%2Fdl-projects","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmoustafamohamed01%2Fdl-projects","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmoustafamohamed01%2Fdl-projects/lists"}