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https://github.com/mariam-badr-mb/mnist-classification

A simple neural network to classify handwritten digits from the MNIST dataset. Build model with activation functions.
https://github.com/mariam-badr-mb/mnist-classification

deep-learning jypyternotebook keras-tensorflow mnist-classification neural-network python

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A simple neural network to classify handwritten digits from the MNIST dataset. Build model with activation functions.

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README

          

# 🧠 MNIST Digit Classification Using Neural Networks

This project builds and trains neural networks on the **MNIST dataset** to classify handwritten digits (0–9).
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## 💡 Objective

Explore how activation functions and regularization affect neural network performance in digit classification.

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## 📊 Techniques Used

- **Data Preprocessing**:
- Normalize pixel values
- One-hot encode labels
- **Build Model **:
- With activation functions
- **Loss & Accuracy Visualization**

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## 🧠 Tools & Libraries

- Python
- `TensorFlow`, `Keras`
- `NumPy`, `Matplotlib`

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## 📁 Dataset

- Dataset: **MNIST Handwritten Digits**
- 60,000 training images and 10,000 test images of digits (0–9)
- Each image is 28x28 pixels in grayscale
- Loaded directly from `keras.datasets.mnist`

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## 📈 Project Workflow

1. **Load & Preprocess Data**
2. **Build Model with Activation**
3. **Train The Model**
4. **Evaluate Final Model**
5. **Visualize Predictions**

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## 🔍 Example Output

- Accuracy Comparison of Models
- Training vs. Validation Loss Plot
- Sample Predictions with True Labels

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## 💾 Output Sample

| Image Index | True Label | Predicted Label |
|-------------|------------|-----------------|
| 0 | 7 | 7 |
| 1 | 2 | 2 |
| 2 | 1 | 1 |

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## 👩‍💻 Author

**Mariam Badr**
Faculty of Computers & Artificial Intelligence, Cairo University
[GitHub](https://github.com/Mariam-Badr-MB) – [LinkedIn](https://www.linkedin.com/in/mariambadr13/)

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## 📜 License

This project is for educational and learning purposes only.