🧠 TensorFlow Example Project

This repository demonstrates a simple yet powerful implementation of machine learning using TensorFlow. It is designed for beginners to intermediate learners who want to understand how neural networks work in practice.

🚀 Features

• Easy-to-understand TensorFlow code
• Clean project structure
• Dataset preprocessing included
• Model training & evaluation
• Visualization of results

📂 Project Structure

tensorflow-example/
│── data/                # Dataset files
│── models/              # Saved models
│── notebooks/           # Jupyter notebooks
│── src/
│   ├── preprocess.py    # Data preprocessing
│   ├── train.py         # Model training
│   ├── evaluate.py      # Model evaluation
│── requirements.txt
│── README.md

⚙️ Installation

Clone the repository:

git clone https://github.com/yourusername/tensorflow-example.git
cd tensorflow-example

Install dependencies:

pip install -r requirements.txt

🧪 Usage

1. Preprocess Data

python src/preprocess.py

2. Train Model

python src/train.py

3. Evaluate Model

python src/evaluate.py

🧠 Model Overview

This project uses a simple neural network built with TensorFlow:

• Input Layer
• Hidden Dense Layers (ReLU)
• Output Layer (Softmax / Sigmoid)

📊 Example Output

• Accuracy: ~90% (depending on dataset)
• Loss visualization included
• Training vs Validation graphs

📌 Requirements

• Python 3.8+
• TensorFlow
• NumPy
• Matplotlib
• Pandas

💡 Learning Goals

By exploring this project, you will learn:

• How TensorFlow works
• Data preprocessing pipeline
• Training and evaluating models
• Basic deep learning concepts

🤝 Contributing

Pull requests are welcome. For major changes, open an issue first to discuss what you would like to change.

📜 License

This project is licensed under the MIT License.