This project implements a Convolutional Neural Network (CNN) to recognize handwritten characters. The goal is to accurately classify images of handwritten digits from the MNIST dataset, a common benchmark in machine learning for handwritten digit recognition.
To run this notebook, you need Python installed on your machine. The required Python libraries include:
Jupyter Notebook TensorFlow Keras NumPy Matplotlib
The MNIST dataset, containing 70,000 images of handwritten digits (0-9), is often used. Each image is a 28x28 pixel grayscale representation of a digit.
The MNIST dataset can be loaded directly from their respective dataset collections using libraries like TensorFlow or Keras.