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README.md

@@ -1,12 +1,74 @@
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-title: Digit Recognition Ui
-emoji: 😻
-colorFrom: indigo
-colorTo: purple
-sdk: gradio
-sdk_version: 5.24.0
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# AI Model Training Project
+
+This project demonstrates a complete machine learning workflow from data preparation to model deployment, using the MNIST dataset with an innovative approach to digit recognition.
+
+## Project Structure
+
+```
+.
+├── data/                  # Dataset storage
+├── models/               # Saved model files
+├── src/                  # Source code
+│   ├── data_preparation.py
+│   ├── model.py
+│   ├── training.py
+│   ├── evaluation.py
+│   └── deployment.py
+├── notebooks/           # Jupyter notebooks for exploration
+├── requirements.txt     # Project dependencies
+└── README.md           # Project documentation
+```
+
+## Setup Instructions
+
+1. Create a virtual environment:
+```bash
+python -m venv venv
+source venv/bin/activate  # On Windows: venv\Scripts\activate
+```
+
+2. Install dependencies:
+```bash
+pip install -r requirements.txt
+```
+
+3. Run the training pipeline:
+```bash
+python src/training.py
+```
+
+## Project Features
+
+- Custom CNN architecture for robust digit recognition
+- Data augmentation techniques
+- Model evaluation and hyperparameter tuning
+- Model deployment pipeline
+- Performance monitoring
+
+## Learning Concepts Covered
+
+1. Data Preprocessing
+   - Data loading and cleaning
+   - Feature engineering
+   - Data augmentation
+
+2. Model Architecture
+   - Custom CNN design
+   - Layer configuration
+   - Activation functions
+
+3. Training Process
+   - Loss functions
+   - Optimizers
+   - Learning rate scheduling
+   - Early stopping
+
+4. Evaluation
+   - Metrics calculation
+   - Cross-validation
+   - Model comparison
+
+5. Deployment
+   - Model saving
+   - Inference pipeline
+   - Performance monitoring