Artificial Intelligence and Neural Networks

Deep Learning

Deep learning, also known as deep structured learning, is a subset of machine learning focused on learning data representations. It typically utilizes gradient descent for training through back propagation. The architecture of deep learning involves multiple layers, including hidden layers in artificial neural networks and sets of propositional formulas. A Deep Neural Network (DNN) is an artificial neural network with multiple hidden layers between the input and output layers. DNN architectures create hierarchical models where an object is represented as a layered composition of simpler elements. These networks are often feed forward neural networks, where data flows from the input layer to the output layer without feedback loops.

Applications of deep learning include:

• Automatic Speech Recognition
• Image Recognition
• Visual Art Processing
• Natural Language Processing (NLP)