Sequential Convolutional Neural Network for handwritten digits recognition trained on MNIST dataset using keras API.
The input data was divided into 90% training set and 10% validation set and the neural network was optimized using Adam Optimizer. tf.keras.losses. SparseCategoricalCrossentropy was used to compute the crossentropy loss between the labels and predictions. The model achieved 97.43% accurary.