Handwritten Digit Recognition using Neural Networks (MNIST)

Built a neural network model to classify handwritten digits using the MNIST CSV dataset.

Improved model performance using:

• Batch Normalization
• Dropout regularization to reduce overfitting

Evaluated the model using:

• Accuracy
• Confusion matrix
• Validation curves

Tools used: Python, TensorFlow, NumPy, Matplotlib.