Power Transformer ML

This project applies machine learning techniques to analyze and predict the performance of electrical power transformers. The goal is to optimize transformer operations, improve reliability, and predict potential failures, utilizing a combination of electrical engineering and machine learning.

Features

• Data preprocessing for transformer datasets
• Machine learning models for predicting transformer performance
• Performance evaluation metrics for model accuracy
• Scalable architecture for power transformer monitoring

Installation

1. Clone the repository:

   git clone [email protected]:SanjoyPator1/power-transformer-ml.git

2. Create and activate the `power-trans` Conda environment
```bash
	conda create -n power-trans python=3.8
conda activate power-trans

3. Install required dependencies

	pip install -r requirements.txt	

Usage

• Add your transformer dataset to the data folder
• Run the Jupyter notebooks for data analysis and model training

Contributing

Feel free to open issues and submit pull requests for improvements.

License

This project is licensed under the MIT License.