Hands-On Predictive AI Modeling Using MATLAB — Implement Naive Bayes Classifiers, k-Nearest Neighbors, and Feedforward Neural Networks

Description

Today, the amount of data generated by both humans and machines far exceeds the ability of humans to absorb, interpret, and make complex decisions based on that data. Artificial Intelligence is the foundation of all machine learning and the future of all complex decision-making processes. 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. Predictive Artificial Intelligence (AI) is a branch of Artificial Intelligence that uses algorithms and statistical models that are based on historical data to anticipate behaviors, make predictions, analyze trends, make classifications, and simulate future events. This book develops predictive techniques. Na•ve Bayes algorithm, Nearest Neighbor algorithm, Neural Networks algorithm for Pattern Recognition, Neural Network algorithm for classification, And Neural Network architectures (Multilayer Perceptron and Radial Basis networks) are included.

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