/IPL-Score-Predictor

An IPL score prediction app built with Flask that uses machine learning models to forecast match scores and outcomes, providing cricket fans with predictive insights and game analysis.

Primary LanguageJupyter NotebookMIT LicenseMIT

IPL Score Predictor

The IPL Score Predictor is a machine learning-based project that predicts the scores of Indian Premier League (IPL) cricket matches. Using historical data and advanced algorithms, this predictor aims to provide insights into the potential scores of upcoming IPL matches.

Features

  • Machine Learning Model: Utilizes a trained model to predict scores based on various features.

  • Data Processing: Cleans and processes historical IPL match data for accurate predictions.

  • User-Friendly Interface: Offers an intuitive interface for users to input match details and get score predictions.

  • Evaluation Metrics: Provides evaluation metrics to assess the model's performance.

Screenshot

Screenshot (60)

Prerequisites

  • Python 3.8
  • Dependencies List -

    Prerequisites

  • Python 3.8
  • Dependencies List:

    • Scikit Learn: A machine learning library in Python.

      • Install: pip install scikit-learn
      • Purpose: Utilized for implementing machine learning models and data preprocessing in the project.

    • Pandas: A powerful data manipulation and analysis library.

      • Install: pip install pandas
      • Purpose: Used for handling and processing structured data.

    • NumPy: A fundamental package for scientific computing with Python.

      • Install: pip install numpy
      • Purpose: Provides support for large, multi-dimensional arrays and matrices, along with mathematical functions to operate on these arrays.

    • Seaborn: A data visualization library based on Matplotlib.

      • Install: pip install seaborn
      • Purpose: Enhances the visual appeal of statistical graphics created with Matplotlib.

    • Matplotlib: A comprehensive library for creating static, interactive, and animated plots.

      • Install: pip install matplotlib
      • Purpose: Essential for generating various types of plots and charts.

    • Datetime: Python module for working with dates and times.

      • Comes with the Python standard library, no separate installation required.
      • Purpose: Used for manipulating dates and times in the project.

    • Flask: A lightweight web application framework.

      • Install: pip install Flask
      • Purpose: Used for building web applications and serving the application in a server environment.

    • Pickle: A module for serializing and deserializing Python objects.

      • Comes with Python standard library, no separate installation required.
      • Purpose: Used for saving and loading machine learning models or other Python objects.

Acknowledgements

  • Kaggle: Thanks to Kaggle for providing historical IPL match data.

  • Flask: Special thanks to the Flask framework for making web development in Python elegant and straightforward.

  • Scikit-learn: We appreciate the Scikit-learn library for providing powerful tools for predictive modeling.

  • NumPy: Heartfelt thanks to the NumPy community for developing a fundamental library that forms the backbone of numerical computing in Python.

  • Pandas: Special appreciation to the Pandas development team for creating an indispensable tool for data manipulation and analysis, making our project more efficient and effective.

  • Matplotlib: A big thanks to the Matplotlib developers for providing an extensive and flexible plotting library, adding a visual dimension to our data exploration and presentation.

  • Seaborn: We express our gratitude to the Seaborn community for enhancing our data visualization capabilities with a high-level interface to Matplotlib, making our plots more aesthetically pleasing and informative.

  • Open Source Community: Gratitude to the broader open-source community for sharing knowledge and fostering collaboration.

Contact

Email : miteshgupta2711@gmail.com

Linkedin : https://www.linkedin.com/in/mitesh-gupta/

Twitter : https://twitter.com/mg_mitesh