/Fundamentals-of-Data-Analysis-Project

Wind Turbine Power Production

Primary LanguageJupyter NotebookMIT LicenseMIT

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

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

  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

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