Advanced Analytics and Artificial Intelligence ApplicationsКНИГИ » ПРОГРАММИНГ
Название: Advanced Analytics and Artificial Intelligence Applications Автор: Ali Soofastaei Издательство: ITExLi Год: 2019 Язык: английский Формат: pdf (true) Размер: 23.7 MB
This book aims to present the application of advanced analytics and AI in different industries as practical tools to develop prediction, optimization, and make decision models.
Computers and machines were developed to reduce time consumption and manual human efforts to complete projects efficiently. With fast-growing technologies in the field, we have finally reached a stage where almost everyone in the world has access to these high technologies. However, this is just a starting phase because future development is taking a more advanced route in the shape of Artificial Intelligence (AI). Although AI is under the computer science umbrella, nowadays there is no field unaffected by this high technology. The overall aim of using intelligence learning methods is to train machines to think intelligently and make decisions in different situations the same as humans. Previously, machines were doing what they were programmed to do, but now with AI, devices can think and behave like a human being.
The opportunities and complexities associated with the digital era can be overwhelming to industries and markets, which face an enormous amount of potential information in each transaction. Being aware of trends in the data pool and benefiting from hidden information has created a new paradigm, redefining the meaning of corporate power. Access to information can make organizations more effective and help them to reach their goals. Big data analytics (BDA) enables industries to describe, diagnose, predict, prescribe, and find hidden growth opportunities, potentially increasing business value. BDA uses advanced analytical techniques to enhance knowledge and improve decision-making by reducing the complexity of exponentially increasing amounts of data. BDA uses novel and sophisticated algorithms to analyze real-time data, resulting in highly accurate analytics. Depending on the problem being solved, these complex algorithms can be allocated to either deep learning or machine learning (ML) approaches.
Contents 1.Introductory Chapter: Advanced Analytics and Artificial Intelligence Applications 2.Bio-Inspired Hybrid Algorithm for Web Services Clustering 3.Smart Material Planning Optimization Problem Analysis 4.A Deep Learning-Based Aesthetic Surgery Recommendation System 5.An Assessment of the Prediction Quality of VPIN 6.Artificial Intelligence Data Science Methodology for Earth Observation
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