The IPL Victory Predictor project utilizes machine learning to forecast match outcomes in the Indian Premier League (IPL) 📈🏆, drawing from a comprehensive dataset spanning from 2008 to 2023, sourced from https://www.kaggle.com/datasets/patrickb1912/ipl-complete-dataset-20082020/data. It's a fun machine learning endeavor tailored for cricket enthusiasts interested in both cricket and machine learning, offering insights into team performance and victory determinants 💪📊
- Scripting Language: Python
- Hosting Platform: Streamlit
The project consists of the following steps:
🧹 Data Cleaning and Manipulation: Prior to constructing the prediction model, extensive data cleaning operations were conducted to ensure result accuracy. This involved removing rows with null values and manipulating existing data to enhance dataset quality, thereby improving model performance.
🔬 Model Creation: A logistic regression model was developed using the refined dataset. Logistic regression, a well-known machine learning algorithm for classification tasks, was chosen for its suitability in predicting IPL team victories. Trained on historical IPL data, the model offers insights into team performance and victory determinants.
💻 User Interface: To enhance accessibility and user-friendliness, a visually appealing user interface was crafted. Users can engage with the IPL Victory Predictor through an intuitive interface, offering input options and displaying predicted outcomes. This UI ensures an enjoyable experience for users keen on exploring IPL team performance and making predictions.
🚀 Deployment with Streamlit: The project was deployed via Streamlit, a robust framework for developing and sharing data applications. By hosting the IPL Victory Predictor on Streamlit, users gain remote access to the application, facilitating convenient exploration of team performance and prediction-making for IPL enthusiasts, data analysts, and cricket aficionados alike.
To run the IPL Victory Predictor on your local system, follow these steps:
Clone the repository to your local machine:
git clone https://github.com/lokesh-cuttamanchi/IPL-Predictor-2024.gitInstall the required dependencies:
pip install -r requirements.txtRun the project:
streamlit run main.py