ARTIFICIAL INTELLIGENCE TOOLS: CLUSTERING AND PATTERN RECOGNITION WITH NEURAL NETWORKS. Examples with MATLAB (ePub)
(Sprache: Englisch)
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...
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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. The availability of large volumes of data and the generalized use of computer tools has transformed research and data analysis, orienting it towards certain specialized techniques encompassed under the generic name of Analytics that includes Multivariate Data Analysis (MDA), Data Mining, Machine Learning and other Business Intelligence techniques. Data Mining (or Machine Learning) can be defined as a process of discovering new and significant relationships, patterns and trends when examining large amounts of data. The techniques of Data Mining pursue the automatic discovery of the knowledge contained in the information stored in an orderly manner in large databases. These techniques aim to discover patterns, profiles and trends through the analysis of data using advanced statistical techniques of multivariate data analysis. Data Mining an Machine Learning uses two types of techniques: predictive techniques (supervised learnig techniques) , which trains a model on known input and output data so that it can predict future outputs, and descriptive techniques (unsupervised learning techniques), which finds hidden patterns or intrinsic structures in input data. Descriptive techniques finds hidden patterns or intrinsic structures in data. It is used to draw inferences from datasets consisting of input data without labeled responses. Clustering is the most common descriptive technique. It is used for exploratory data analysis to find hidden patterns or groupings in data. Applications for clustering include gene sequence analysis, market research, and object recognition. This book develops classification descriptive techniques with neural networks.
Bibliographische Angaben
- Autor: César Pérez López
- 2023, Englisch
- Verlag: Lulu.com
- ISBN-10: 1446786668
- ISBN-13: 9781446786666
- Erscheinungsdatum: 27.07.2023
Abhängig von Bildschirmgröße und eingestellter Schriftgröße kann die Seitenzahl auf Ihrem Lesegerät variieren.
eBook Informationen
- Dateiformat: ePub
- Größe: 2.88 MB
- Ohne Kopierschutz
Sprache:
Englisch
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