{"id":25486610,"url":"https://github.com/mahdimotamedi/ai-examples","last_synced_at":"2026-04-13T02:04:37.455Z","repository":{"id":278203795,"uuid":"934856542","full_name":"mahdimotamedi/Ai-Examples","owner":"mahdimotamedi","description":"AI Examples Repository showcasing machine learning and deep learning examples using Scikit-Learn and TensorFlow. 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This repository contains various **machine learning** and **deep learning** examples using **Scikit-Learn** and **TensorFlow**.\n\n## 📌 About\nThis repository includes multiple AI-related examples, covering topics like:\n✅ **Supervised Learning** (Classification, Regression)\n✅ **Neural Networks (Deep Learning)**\n✅ **Convolutional Neural Networks (CNNs)**\n✅ **Model Training \u0026 Prediction**\n\nAll examples are implemented in **Python 3.11** and demonstrate how to build and train machine learning models efficiently.\n\n---\n\n## 📂 Examples Included\n### 1️⃣ **Logistic Regression with Scikit-Learn**\n- Implements **classification** using **Logistic Regression**.\n- Uses **Iris Dataset** from `sklearn.datasets`.\n- Demonstrates **data preprocessing, model training, evaluation, and predictions**.\n\n### 2️⃣ **CNN for Image Classification with TensorFlow**\n- Builds a **Convolutional Neural Network (CNN)** using `tensorflow.keras`.\n- Trains on the **CIFAR-10 dataset** to classify images into **10 categories**.\n- Includes **data normalization, model architecture, training, and custom image prediction**.\n- Supports **saving and loading models** to avoid retraining every time.\n\n### 3️⃣ **Transformer Model for Sentiment Analysis with TensorFlow**\n- Implements a **Transformer-based neural network** using `tensorflow.keras`.\n- Trains on the **IMDB Movie Reviews Dataset** for binary sentiment classification (**positive** or **negative**).\n- Includes:\n  - **Data downloading** and **preprocessing**.\n  - Custom **Transformer architecture** with positional embeddings and multi-head attention.\n  - Functions for **model training**, **prediction**, and **evaluation**.\n---\n\n## ⚙️ Installation \u0026 Setup\nBefore running the code, install the required dependencies:\n\n```sh\npip install numpy pandas matplotlib scikit-learn tensorflow opencv-python pillow\n```\n\nEnsure that you're using **Python 3.11**:\n\n```sh\npython --version\n```\n\n---\n\n## 🚀 Running the Examples\n### **Run each of the examples individually and see the result.**\n```sh\npython linear_regression.py\n```\n\n---\n\n## 📌 Saving \u0026 Loading Models\nTo avoid re-training the model every time, the \"cnn_image_classification_custom_image.py\" script automatically **saves** the trained model as:\n```\ncifar10_model.h5\n```\nIf the model is already trained, it will be **loaded automatically** instead of re-training.\n\n---\n\n## 🎯 Future Improvements\n- Adding **Object Detection models**.\n- Implementing **Reinforcement Learning** algorithms.\n\n---\n\n## 📝 License\nThis project is open-source under the **MIT License**. Feel free to use, modify, and contribute! 🚀\n\n---\n\n🔗 **Stay Connected**\nFor updates and discussions, feel free to **follow the repository** or **open an issue** if you have any questions!\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmahdimotamedi%2Fai-examples","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmahdimotamedi%2Fai-examples","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmahdimotamedi%2Fai-examples/lists"}