Fundamentals of Deep Neural Networks - application based on MLPS

Abstract

Deep Neural Networks have become one of the center pieces in the field of machine learning, mostly due to accuracy, practical applications and efficiency. These algorithms have proven to be the state of the art in solving tasks such as regressions, clustering and image classification. The purpose of this project was to study and implement deep learning applications using one of the most simple and powerful networks: the multilayer perceptron. Therefore, the project started with a theorical approach and built towards the design of an MLP-based deep neural network capable of classifying hand-written digits.