Project Title

Bulls Demand Predictor - polynomial regression model which calculates how much bulls are needed based on historical data which can be directly related to population, this project includes a web interface and API for making predictions and visualising them

Description

this predictor uses polynomial regression to calculate the number of bulls required in relation to the year or other features. it allows users of it to:

• select features and targets from a wrangled dataset
• perform polynomial regression with customizable degrees
• predict values with a given input
• vizualise the regression curve and actual data points

Getting Started

Dependencies

ensure these following dependencies

• numpy
• matplotlib
• pandas
• scikit-learn
• keras
• tensorflow
• pydot
• graphviz
• pydot-ng
• pillow
• pydotplus

you can install these libraries using

pip install -r requirements.txt

Installing

Installing Clone the repository: git clone cd Ensure the training_data.csv and testing_data.csv files are in the root directory. python polynomial_regression_api.py Run the Flask application:

Executing program

• 1.start the flask server:

python polynomial_regression_api.py

• 2.open your browser and type in the url

http://127.0.0.1:5000

• 3.Use the web interface to:

• • select a feature e.g(YEAR) and a target- Select features and targets from a wrangled dataset.

• Perform polynomial regression with customizable degrees.

• Predict values with a given input.

• Visualize the regression curve and actual data points.

Help

If you encounter any issues, ensure the following:

• The training_data.csv and testing_data.csv files are correctly formatted and present in the root directory.
• All required dependencies are installed.

For debugging, you can run the Flask application in debug mode:

command to run if program contains helper info

Authors

• Dashiell Johnson Contributors names and contact info

ex. Mr Jones ex. @benpaddlejones

Version History

• 0.2
  • Various bug fixes and optimizations
  • See commit change or See release history or see branch
• 0.1
  • Initial Release

License

This project is licensed under the [Dashiell Johnson] License - see the LICENSE.md file for details

Acknowledgments

Inspiration, code snippets, etc.

• Github md syntax

• TempeHS Jupyter-Notebook template

• Scikit-learn Documentation

• Flask Documentation

• Matplotlib Documentation