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Description
TOOLS FOR ARTIFICIAL INTELLIGENCE: NEURAL NETWORKS AND APPLICATIONS Examples with MatlabArtificial Intelligence combines mathematical algorithms and techniques from Machine Learning, Deep Learning and Big Data to extract the knowledge contained in the data and present it in an understandable and automatic way. Neural networks and their applications are a fundamental tool to develop work in Artificial Intelligence. Among the most interesting predictive models are the neural networks. MATLAB implementrs the Neural Network Toolbox
Artificial Intelligence combines mathematical algorithms and techniques from Machine Learning, Deep Learning and Big Data to extract the knowledge contained in the data and present it in an understandable and automatic way. Neural networks and their applications are a fundamental tool to develop work in Artificial Intelligence. Among the most interesting predictive models are the neural networks. MATLAB implementrs the Neural Network Toolbox specialized in the techniques of analytics based on neural networks. Throughout this book the techniques of analytics based on neural networks are developed using MATLAB software and in concrete Neural Network Toolbox. The Neural Network Toolbox software uses the network object to store all of the information that defines a neural network. MATLAB has the tool Neural Network Toolbox (Deep Learning Toolbox from 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.
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