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Big Data Intelligence for Smart Applications

Автор: Limpopo5 от 2022-01-22, 00:03:20
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Big Data Intelligence for Smart ApplicationsНазвание: Big Data Intelligence for Smart Applications
Автор: Youssef Baddi, Youssef Gahi, Yassine Maleh
Издательство: Springer
Год: 2022
Страниц: 343
Язык: английский
Формат: pdf (true), epub
Размер: 38.9 MB

Today, the use of Machine Intelligence, expert systems, and analytical technologies combined with Big Data is the natural evolution of both disciplines. As a result, there is a pressing need for new and innovative algorithms to help us find effective and practical solutions for smart applications such as smart cities, IoT, healthcare, and cybersecurity. This book presents the latest advances in Big Data intelligence for smart applications. It explores several problems and their solutions regarding computational intelligence and big data for smart applications. It also discusses new models, practical solutions,and technological advances related to developing and transforming cities through Machine Intelligence and Big Data models and techniques. This book is helpful for students and researchers as well as practitioners. It is worth noting that technologies such as Artificial intelligence and Big Data are evolving even faster. They are rapidly growing by holding great promise for many sectors. The real revolutionary potential of these technologies mainly relies on their convergence. Big Data and Artificial Intelligence are two technologies that are inextricably linked, to the point that we can think about Big Data Intelligence. AI has become ubiquitous in many industries where intelligent programs relying on big data transform decision-making.

Machine Learning: Neural Networks, Decision Trees and Support Vector Machine with IBM SPSS Modeler

Автор: Limpopo5 от 2022-01-18, 17:51:35
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Machine Learning: Neural Networks, Decision Trees and Support Vector Machine with IBM SPSS ModelerНазвание: Machine Learning: Neural Networks, Decision Trees and Support Vector Machine with IBM SPSS Modeler
Автор: L. Marvin
Издательство: Lulu.com
Год: 2021
Страниц: 275
Язык: английский
Формат: epub
Размер: 13.0 MB

Machine Learning techniques are intended to extract the knowledge contained in the data through models and other appropriate techniques. Within Machine Learning techniques there are two fundamental types: supervised learning techniques and unsupervised learning techniques. Supervised learning techniques include all those that use a model in which there are dependent variables and independent variables. The purpose of these techniques is usually prediction or classification of both at the same time. Neural networks, decision trees, and SVM models are supervised learning machine learning techniques for prediction and classification. It is precisely these techniques that are developed in this book using IBM SPSS Modeler software.

Rhythmic Advantages in Big Data and Machine Learning

Автор: Limpopo5 от 2022-01-13, 08:20:53
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Rhythmic Advantages in Big Data and Machine LearningНазвание: Rhythmic Advantages in Big Data and Machine Learning
Автор: Anirban Bandyopadhyay, Kanad Ray
Издательство: Springer
Год: 2022
Страниц: 270
Язык: английский
Формат: pdf (true)
Размер: 10.15 MB

The current book in the series of Systems in Rhythm Engineering, SRE, compiles rhythms from Big data in pure computation, astrophysics to basic biological structures. In today’s world, anything and everything is data and we generate voluminous data almost every passing second which actually gave birth to “Big Data”. The phrase “Big Data” which buzzes around us everywhere, is applied to a specific type of data that has certain traits. However, this phrase has been over used and often incorrectly, which is why itis difficult to gauge its true meaning. For commoners, it is very difficult to understand if Big Data is a tool or a technology or just a buzzword used by data scientists to scare us. Another concern is if Big Data really has the potential to usher in dramatic changes or will the hype fade away with time. In any case, over the past few years, Big Data has become an integral part of several industries and in many cases has shown the potential to be a game-changer.

Applied Biomedical Engineering Using Artificial Intelligence and Cognitive Models

Автор: Limpopo5 от 2021-12-11, 03:42:43
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Applied Biomedical Engineering Using Artificial Intelligence and Cognitive ModelsНазвание: Applied Biomedical Engineering Using Artificial Intelligence and Cognitive Models
Автор: Jorge Garza-Ulloa
Издательство: Academic Press, Elsevier
Год: 2022
Страниц: 705
Язык: английский
Формат: pdf (true)
Размер: 37.1 MB

Applied Biomedical Engineering Using Artificial Intelligence and Cognitive Models focuses on the relationship between three different multidisciplinary branches of engineering: Biomedical Engineering, Cognitive Science and Computer Science through Artificial Intelligence models. Applied Biomedical Engineering Using Artificial Intelligence and Cognitive Models provides readers with the study of injuries, illness, and neurological diseases of the human body through Artificial Intelligence using Machine Learning (ML), Deep Learning (DL) and Cognitive Computing (CC) models based on algorithms developed with MATLAB and IBM Watson.

Genetic Programming for Production Scheduling

Автор: Limpopo5 от 2021-11-13, 15:06:58
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Genetic Programming for Production SchedulingНазвание: Genetic Programming for Production Scheduling
Автор: Fangfang Zhang, Su Nguyen, Yi Mei
Издательство: Springer
Серия: Machine Learning: Foundations, Methodologies, and Applications
Год: 2021
Страниц: 357
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

Scheduling, i.e., the assignment of resources to tasks and their sequencing, is an important challenge in many areas, including manufacturing, health care, construction, and even when scheduling processes within a computer. Given its wide ranging importance, it is not surprising that scheduling is one of the oldest and most researched topics in Operational Research. Evolutionary learning applies evolutionary computation to address optimisation problems in Machine Learning. Evolutionary computation is a computational intelligence technique inspired by natural evolution based on population. Evolutionary computation consists of a family of algorithms. The success of evolutionary computation relies on the improvement of individuals generation by generation. There are two main categories in EC, which are evolutionary algorithms such as genetic algorithms, genetic programming, evolution strategies, and evolutionary programming, and swarm intelligence such as particle swarm optimisation and ant colony optimisation. Evolutionary algorithms, especially genetic programming, are the focus in this book.

Physics of Data Science and Machine Learning

Автор: Limpopo5 от 2021-11-04, 15:30:16
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Physics of Data Science and Machine LearningНазвание: Physics of Data Science and Machine Learning
Автор: Ijaz A. Rauf
Издательство: CRC Press
Год: 2022
Страниц: 211
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB

Physics of Data Science and Machine Learning links fundamental concepts of physics to Data Science, Machine Learning and Artificial Intelligence for physicists looking to integrate these techniques into their work. This book is written explicitly for physicists, marrying quantum and statistical mechanics with modern data mining, Data Science, and Machine Learning. It also explains how to integrate these techniques into the design of experiments, whilst exploring neural networks and Machine Learning building on fundamental concepts of statistical and quantum mechanics. This book is a self-learning tool for physicists looking to learn how to utilize data science and Machine Learning in their research. It will also be of interest to computer scientists and applied mathematicians, alongside graduate students looking to understand the basic concepts and foundations of Data Science, Machine Learning, and Artificial Intelligence.

Discriminating Data: Correlation, Neighborhoods, and the New Politics of Recognition

Автор: Limpopo5 от 2021-11-03, 20:49:14
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Discriminating Data: Correlation, Neighborhoods, and the New Politics of RecognitionНазвание: Discriminating data: Correlation, Neighborhoods, and the New Politics of Recognition
Автор: Wendy Hui Kyong Chun, Alex Barnett
Издательство: The MIT Press
Год: 2021
Страниц: 344
Язык: английский
Формат: epub
Размер: 10.1 MB

How Big Data and Machine Learning encode discrimination and create agitated clusters of comforting rage. In Discriminating Data, Wendy Hui Kyong Chun reveals how polarization is a goal—not an error—within Big Data and Machine Learning. These methods, she argues, encode segregation, eugenics, and identity politics through their default assumptions and conditions. Correlation, which grounds Big Data’s predictive potential, stems from twentieth-century eugenic attempts to “breed” a better future.

The Digital Journey of Banking and Insurance, Volume II: Digitalization and Machine Learning

Автор: Limpopo5 от 2021-10-27, 20:42:43
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The Digital Journey of Banking and Insurance, Volume II: Digitalization and Machine LearningНазвание: The Digital Journey of Banking and Insurance, Volume II: Digitalization and Machine Learning
Автор: Volker Liermann, Claus Stegmann
Издательство: Palgrave Macmillan
Год: 2021
Страниц: 361
Язык: английский
Формат: pdf (true), epub
Размер: 51.1 MB

This book, the second one of three volumes, gives practical examples by a number of use cases showing how to take first steps in the digital journey of banks and insurance companies. The angle shifts over the volumes from a business-driven approach in “Disruption and DNA” to a strong technical focus in “Data Storage, Processing and Analysis”, leaving “Digitalization and Machine Learning Applications” with the business and technical aspects in-between. This second volume mainly emphasizes use cases as well as the methods and technologies applied to drive digital transformation (such as processes, leveraging computational power and Machine Learning models).

Machine Learning Control by Symbolic Regression

Автор: Limpopo5 от 2021-10-23, 20:53:07
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Machine Learning Control by Symbolic RegressionНазвание: Machine Learning Control by Symbolic Regression
Автор: Askhat Diveev
Издательство: Springer
Год: 2021
Страниц: 162
Язык: английский
Формат: pdf (true), epub
Размер: 14.2 MB

This book provides comprehensive coverage on a new direction in computational mathematics research: automatic search for formulas. Formulas must be sought in all areas of science and life: these are the laws of the universe, the macro and micro world, fundamental physics, engineering, weather and natural disasters forecasting; the search for new laws in economics, politics, sociology. Accumulating many years of experience in the development and application of numerical methods of symbolic regression to solving control problems, the authors offer new possibilities not only in the field of control automation, but also in the design of completely different optimal structures in many fields.

Text Data Mining

Автор: Limpopo5 от 2021-05-23, 23:26:23
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Text Data MiningНазвание: Text Data Mining
Автор: Chengqing Zong, Rui Xia
Издательство: Springer, Tsinghua University Press
Год: 2021
Страниц: 363
Язык: английский
Формат: pdf (true), epub
Размер: 25.7 MB

Focuses on text data mining from an NLP perspective. This book discusses various aspects of text data mining. Unlike other books that focus on Machine Learning (ML) or databases, it approaches text data mining from a natural language processing (NLP) perspective. Text mining is a confluence of natural language processing, data mining, Machine Learning, and statistics used to mine knowledge from unstructured text. There have already been multiple textbooks dedicated to data mining, Machine Learning, statistics, and natural language processing. However, we seriously lack textbooks on text mining that systematically introduce important topics and up-to-date methods for text mining.

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