https://github.com/mahdimotamedi/ai-examples
AI Examples Repository showcasing machine learning and deep learning examples using Scikit-Learn and TensorFlow.
https://github.com/mahdimotamedi/ai-examples
ai deep-learning machine-learning nerual-networks scikit-learn tensorflow
Last synced: 2 months ago
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AI Examples Repository showcasing machine learning and deep learning examples using Scikit-Learn and TensorFlow.
- Host: GitHub
- URL: https://github.com/mahdimotamedi/ai-examples
- Owner: mahdimotamedi
- Created: 2025-02-18T14:13:52.000Z (over 1 year ago)
- Default Branch: master
- Last Pushed: 2025-02-18T14:52:13.000Z (over 1 year ago)
- Last Synced: 2025-02-18T15:29:03.475Z (over 1 year ago)
- Topics: ai, deep-learning, machine-learning, nerual-networks, scikit-learn, tensorflow
- Language: Python
- Homepage:
- Size: 9.77 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# 🚀 AI Examples Repository
Welcome to the **AI Examples Repository**! This repository contains various **machine learning** and **deep learning** examples using **Scikit-Learn** and **TensorFlow**.
## 📌 About
This repository includes multiple AI-related examples, covering topics like:
✅ **Supervised Learning** (Classification, Regression)
✅ **Neural Networks (Deep Learning)**
✅ **Convolutional Neural Networks (CNNs)**
✅ **Model Training & Prediction**
All examples are implemented in **Python 3.11** and demonstrate how to build and train machine learning models efficiently.
---
## 📂 Examples Included
### 1️⃣ **Logistic Regression with Scikit-Learn**
- Implements **classification** using **Logistic Regression**.
- Uses **Iris Dataset** from `sklearn.datasets`.
- Demonstrates **data preprocessing, model training, evaluation, and predictions**.
### 2️⃣ **CNN for Image Classification with TensorFlow**
- Builds a **Convolutional Neural Network (CNN)** using `tensorflow.keras`.
- Trains on the **CIFAR-10 dataset** to classify images into **10 categories**.
- Includes **data normalization, model architecture, training, and custom image prediction**.
- Supports **saving and loading models** to avoid retraining every time.
### 3️⃣ **Transformer Model for Sentiment Analysis with TensorFlow**
- Implements a **Transformer-based neural network** using `tensorflow.keras`.
- Trains on the **IMDB Movie Reviews Dataset** for binary sentiment classification (**positive** or **negative**).
- Includes:
- **Data downloading** and **preprocessing**.
- Custom **Transformer architecture** with positional embeddings and multi-head attention.
- Functions for **model training**, **prediction**, and **evaluation**.
---
## ⚙️ Installation & Setup
Before running the code, install the required dependencies:
```sh
pip install numpy pandas matplotlib scikit-learn tensorflow opencv-python pillow
```
Ensure that you're using **Python 3.11**:
```sh
python --version
```
---
## 🚀 Running the Examples
### **Run each of the examples individually and see the result.**
```sh
python linear_regression.py
```
---
## 📌 Saving & Loading Models
To avoid re-training the model every time, the "cnn_image_classification_custom_image.py" script automatically **saves** the trained model as:
```
cifar10_model.h5
```
If the model is already trained, it will be **loaded automatically** instead of re-training.
---
## 🎯 Future Improvements
- Adding **Object Detection models**.
- Implementing **Reinforcement Learning** algorithms.
---
## 📝 License
This project is open-source under the **MIT License**. Feel free to use, modify, and contribute! 🚀
---
🔗 **Stay Connected**
For updates and discussions, feel free to **follow the repository** or **open an issue** if you have any questions!