Collection of tensorflow notebooks tutorials for implementing some basic Deep Learning architectures.

Python notebooks for face recognition of 12 people wearing face masks as a 12-class classification task.

This notebook consists of code used to train a neural network architecture to classify the digits along with some ML algorithms.

This repository focuses on handwritten digit recognition using the MNIST dataset. It includes implementations of Logistic Regression, MLP, and LeNet-5 in PyTorch, organized into folders for reports, flowcharts, scripts, and notebooks, with detailed instructions for preprocessing and training.

On this notebook, I compared between MNIST dataset and CIFAR-10 with applying LeNet-5 architecture on both of them, and it results that LeNet-5 works better with MNIST as it's grayscale dataset, the architecture is used for recognizing the handwritten and machine-printed characters.