#The file "MNIST Neural Network.ipynb" is a Jupyter Notebook that demonstrates the implementation of a neural network for the MNIST digit recognition task.
#The notebook includes:
#Code to load and preprocess the MNIST dataset. #Functions to initialize neural network parameters, perform forward propagation, apply activation functions (ReLU and softmax), and compute backpropagation. #A gradient descent function to train the neural network. #Helper functions to visualize training examples and test predictions. #The notebook trains a neural network on the MNIST dataset and evaluates its performance, including printing predictions and true labels for specific examples.