This project focuses on building and training Convolutional Neural Networks (CNNs) to address two distinct classification problems:
Leaf Disease Classification: Identifying various diseases in leaves using image data with a TensorFlow CNN. MNIST Digit Recognition: Recognizing handwritten digits from the MNIST dataset using a CNN built from scratch. The project aims to demonstrate the versatility and effectiveness of CNNs in handling different types of image classification tasks.