This project is a Python application that uses machine learning to recognize handwritten digits. The application has a user interface that allows the user to write a number on a blank canvas. The application then uses a trained machine learning model to predict the number that the user has written.
To run the application, you will need to have Python 3 installed. You can then install the necessary dependencies by running the following command:
pip install -r requirements.txt
Once you have installed the dependencies, you can run the application by running the following command:
python main.py
#User Interface The user interface is a simple canvas where the user can write a number. The canvas is cleared after each prediction. The application also displays the predicted number below the canvas.
#Model The model used by the application is a convolutional neural network (CNN). The CNN was trained on the MNIST dataset, which is a collection of handwritten digits. The MNIST dataset contains 60,000 training images and 10,000 test images.
Accuracy The accuracy of the model on the MNIST dataset is 98.5%. This means that the model correctly predicts the number in 98.5% of the case.
#Author This project was created by PANNAGA PS and team