Wind Turbine Power Production

[Project assessment for Fundamentals of Data Analysis - GMIT 2020]

This repository contains two models, Simple Linear Regression and Polynomial Regression, that make predictions of wind turbine power from given wind speed using the data set powerproduction as a basis. There are two implementations of each model using NumPy and SciPy libraries.

Submitted by: Olga Rozhdestvina (Student No: G00387844)

Lecturer: Ian McLoughlin

Programming Language used: Python

Set up

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Applications used for completion of the project are The Jupyter Notebook and cmder

Distribution of the Python used is Anaconda Python distribution

How to run the code

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1. Make sure that you have Python installed
2. Download or clone current repository "Fundamentals-of-Data-Analysis-Project"
3. Open Command Interpreter and get into correct directory
4. Install packages by running pip install -r requirements.txt (recommended through virtual environment to avoid possible break of system tools or other projects)
5. Run Jupyter notebook
6. On the home page of opened Jupyter server select Power_production_models.ipynb

License

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This project is licensed under the MIT License - see the LICENSE.md file for details.