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Power Analytics - Regression Model for Energy Shortfall Prediction

Project Overview

Power Analytics is a data science company hired by the government of Spain to provide solutions using regression models for their energy-related challenges. The focus of the project is to analyze and predict the daily energy shortfall in Spain, considering both fossil fuel and renewable energy sources.

Problem Statement

The supply of electricity is crucial for the well-being of citizens, and there is a growing need to balance the use of non-renewable and renewable energy sources. The government of Spain is keen on expanding its renewable energy infrastructure and requires insights into the trends and patterns of energy generation.

Data

The project utilizes a dataset stored in the 'train.csv' document, containing information such as time, weather features (wind speed, humidity, etc.), and energy-related variables (load shortfall). The goal is to model the daily energy shortfall as a function of various city-specific weather features.

Team

  • Team Leader: Kamogelo Ramodubjane Sete
    Email

  • Project Manager: Thabo Tladi
    Email

Data Scientists

Project Resources

Project Scope

The project aims to:

  1. Analyze the trends and patterns of energy generation in Spain.
  2. Develop a regression model to predict daily energy shortfalls.
  3. Provide valuable insights for the government's renewable energy infrastructure investments.

Getting Started

To run the regression model and explore the project:

  1. Clone the GitHub repository.
  2. Review the data in the 'train.csv' document for insights.
  3. Collaborate with the team using the Trello board for task management.

Contact

For inquiries and collaboration opportunities, please contact:

  • Kamogelo Ramodubjane Sete (Team Leader): Email
  • Thabo Tladi (Project Manager): Email

We look forward to contributing to the sustainable energy goals of Spain through our regression modeling expertise!

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