This project is an implementation of a deep learning model for recognizing handwritten digits using the MNIST dataset. The model is built using Python and TensorFlow.
The Digits Recognition project aims to develop a machine learning model capable of accurately identifying handwritten digits. It utilizes a convolutional neural network (CNN) architecture to achieve high accuracy in digit recognition.
- Training a deep learning model to recognize handwritten digits.
- Evaluating the model's accuracy on a test dataset.
- Predicting digits in real-time using the trained model.
- Visualizing sample predictions.
- Python 3.x
- TensorFlow
- NumPy
- Matplotlib