/Number-Recognition

Bharat Data Science Intern

Primary LanguageJupyter Notebook

Number-Recognition

Bharat Data Science Intern

Handwritten digit recognition system not only detects scanned images of handwritten digits.Handwritten digit recognition using MNIST dataset is a major project made with the help of Neural Network. It basically detects the scanned images of handwritten digits.

Handwritten Digit Recognition using Neural Networks

  • This project demonstrates the implementation of a neural network-based system for recognizing handwritten digits. Trained on the well-known MNIST dataset, which consists of scanned images of handwritten digits, the system achieves accurate classification results.

  • Using Python and the Keras library, a neural network model is constructed with two hidden layers and ReLU activation functions. The model is trained on the MNIST dataset, optimizing its performance through the Adam optimizer and categorical cross-entropy loss.

  • The trained model's accuracy is evaluated on a separate test dataset, providing insights into its effectiveness in recognizing handwritten digits. The achieved accuracy score showcases the model's reliability.

  • Additionally, the project includes an example of using the trained model to predict the digit in a single image. By passing the image through the neural network, the predicted digit is obtained, showcasing the system's capability for individual digit recognition.