This project aims to predict the outcome of cricket matches using deep learning models. By leveraging historical match data, player statistics, and various match-related features, the model predicts whether a given team will win or lose a cricket match.
- Data Preprocessing: Cleans and prepares historical cricket data for model training, handling missing values and feature engineering.
- Deep Learning Model: Trains a deep learning model using TensorFlow/Keras for predicting match outcomes based on multiple input features.
- Prediction: Predicts match outcomes (win/loss) for upcoming cricket matches using the trained model.
- Visualization: Displays visualizations such as accuracy and loss curves, as well as predictions for upcoming matches.
The model utilizes publicly available datasets containing cricket match details, player statistics, and other relevant features. You can source the dataset from platforms like Kaggle or use custom CSV files.
- Clone this repository to your local machine:
git clone https://github.com/Mahesh7741/Cricket-Match-Winning-Prediction-.git
- Navigate to the project directory:
cd Cricket-Match-Winning-Prediction-- Install the necessary dependencies using requirements.txt:
pip install -r requirements.txt
- Technologies Used Python Flask TensorFlow / Keras Pandas NumPy Scikit-learn Matplotlib Seaborn
Here is a sample README.md file for your project:
markdown Copy code
This project aims to predict the outcome of cricket matches using deep learning models. By leveraging historical match data, player statistics, and various match-related features, the model predicts whether a given team will win or lose a cricket match.
- Data Preprocessing: Cleans and prepares historical cricket data for model training, handling missing values and feature engineering.
- Deep Learning Model: Trains a deep learning model using TensorFlow/Keras for predicting match outcomes based on multiple input features.
- Prediction: Predicts match outcomes (win/loss) for upcoming cricket matches using the trained model.
- Visualization: Displays visualizations such as accuracy and loss curves, as well as predictions for upcoming matches.
The model utilizes publicly available datasets containing cricket match details, player statistics, and other relevant features. You can source the dataset from platforms like Kaggle or use custom CSV files.
- Clone this repository to your local machine:
git clone https://github.com/Mahesh7741/Cricket-Match-Winning-Prediction-.git
Navigate to the project directory:
bash Copy code cd Cricket-Match-Winning-Prediction- Install the necessary dependencies using requirements.txt:
bash Copy code pip install -r requirements.txt Technologies Used Python Flask TensorFlow / Keras Pandas NumPy Scikit-learn Matplotlib Seaborn Usage Prepare the dataset and load it into the model. Train the model by running the training script. Use the trained model to predict future match outcomes.