DEEP LEARNING AND CONVOLUTIONAL NEURAL NETWORKS. MATLAB APPLICATIONS

Deep Learning (translated as deep learning) is a subset of machine learning based on artificial neural networks. The process of this learning is called deep because this network structure consists of having multiple inputs, outputs and hidden layers. Each layer contains units that transform the input data into information, and in this way, the next layer can use it for a certain predictive task. In this way, a machine can learn through its own data processing. MATLAB has the tool Neural Network Toolbox (Deep Leraning toolbox fron release 18) that provides algorithms, functions, and apps to create, train, visualize, and simulate neural networks. You can perform classification, regression, clustering, dimensionality reduction, time-series forecasting, and dynamic system modeling and control. The toolbox includes convolutional neural network and autoencoder deep learning algorithms for image classification and feature learning tasks. To speed up training of large data sets, you can distribute computations and data across multicore processors, GPUs, and computer clusters using Parallel Computing Toolbox.