https://github.com/shahsanjanav/dl-waterquality-classifier

Deep learning project to classify water quality using a PyTorch neural network and real-world data.
https://github.com/shahsanjanav/dl-waterquality-classifier

classification deep-learning deep-neural-networks jupyter-notebook machine-learning python3 pytorch water-quality

Last synced: 3 months ago
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Deep learning project to classify water quality using a PyTorch neural network and real-world data.

• Host: GitHub
• URL: https://github.com/shahsanjanav/dl-waterquality-classifier
• Owner: shahsanjanav
• License: mit
• Created: 2025-06-04T00:20:21.000Z (4 months ago)
• Default Branch: main
• Last Pushed: 2025-06-04T00:27:20.000Z (4 months ago)
• Last Synced: 2025-06-04T07:59:51.870Z (4 months ago)
• Topics: classification, deep-learning, deep-neural-networks, jupyter-notebook, machine-learning, python3, pytorch, water-quality
• Language: Jupyter Notebook
• Homepage:
• Size: 1000 KB
• Stars: 0
• Watchers: 0
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

          
# 🌊 Water Quality Classifier using PyTorch

![Python](https://img.shields.io/badge/Python-3.10-blue?logo=python)

![PyTorch](https://img.shields.io/badge/PyTorch-2.0+-red?logo=pytorch)

![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)

A deep learning-based binary classification project to predict water quality using a 3-layer dense neural network built in PyTorch, trained on normalized water quality data.

---

## 📁 Project Structure

```

DL-WaterQuality-Classifier/

├── DL_WaterQuality.ipynb  	                  # Main training/testing notebook

├── water_quality.csv                             # Dataset file

├── requirements.txt                              # Python dependencies

├── README.md                                     # Project overview

└── .gitignore                                    # Git exclusion rules

```

---

## 📌 Features

- Clean and preprocess water quality dataset

- Normalize features

- Build and train a deep neural network in PyTorch

- Evaluate performance with accuracy and loss plots

---

## 🚀 Getting Started

### 1. Clone the Repository

```bash

git clone https://github.com/shahsanjanav/DL-WaterQuality-Classifier.git

cd DL-WaterQuality-Classifier

```

### 2. Install Dependencies

```bash

pip install -r requirements.txt

```

### 3. Launch the Notebook

```bash

jupyter notebook DL_WaterQuality.ipynb

```

---

## 🧠 Model Architecture

- Input Layer: Based on number of features

- Hidden Layers: Dense + ReLU + Dropout

- Output Layer: Sigmoid activation for binary classification

- Loss: Binary Cross Entropy Loss

- Optimizer: Adam

---

## 📊 Dataset

The `water_quality.csv` dataset contains multiple physical and chemical water parameters labeled for classification.

---

## 🛠 Built With

- [Python 3.10+](https://www.python.org/)

- [PyTorch](https://pytorch.org/)

- [Jupyter Notebook](https://jupyter.org/)

- [pandas, numpy, sklearn, matplotlib](https://pypi.org/)

---

## 📄 License

MIT License © 2025 Sanjana Shah

---

## 👤 Author

**Sanjana Shah**  

✨ Machine Learning & Generative AI Enthusiast  

📫 Connect on [LinkedIn](https://www.linkedin.com/in/sanjanavshah)

GitHub: [@shahsanjanav](https://github.com/shahsanjanav)

---

⭐ If you like this project, consider starring it on GitHub!