Data Analytics And Computational Intelligence Novel Models Algorithms And Applications

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Data Analytics and Computational Intelligence: Novel Models, Algorithms and Applications

Gilberto Rivera,Laura Cruz-Reyes,Bernabé Dorronsoro,Alejandro Rosete
Data Analytics and Computational Intelligence Novel Models Algorithms and Applications Book PDF

Author : Gilberto Rivera,Laura Cruz-Reyes,Bernabé Dorronsoro,Alejandro Rosete
Publisher : Springer Nature
Page : 597 pages
File Size : 42,9 Mb
Release : 2023-10-20
Category : Computers
ISBN : 9783031383250

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Data Analytics and Computational Intelligence: Novel Models, Algorithms and Applications by Gilberto Rivera,Laura Cruz-Reyes,Bernabé Dorronsoro,Alejandro Rosete Pdf

In the age of transformative artificial intelligence (AI), which has the potential to revolutionize our lives, this book provides a comprehensive exploration of successful research and applications in AI and data analytics. Covering innovative approaches, advanced algorithms, and data analysis methodologies, this book addresses complex problems across topics such as machine learning, pattern recognition, data mining, optimization, and predictive modeling. With clear explanations, practical examples, and cutting-edge research, this book seeks to expand the understanding of a wide readership, including students, researchers, practitioners, and technology enthusiasts eager to explore these exciting fields. Featuring real-world applications in education, health care, climate modeling, cybersecurity, smart transportation, conversational systems, and material analysis, among others, this book highlights how these technologies can drive innovation and generate competitive advantages.

Computational Intelligence Applications in Business Intelligence and Big Data Analytics

Vijayan Sugumaran,Arun Kumar Sangaiah,Arunkumar Thangavelu
Computational Intelligence Applications in Business Intelligence and Big Data Analytics Book PDF

Author : Vijayan Sugumaran,Arun Kumar Sangaiah,Arunkumar Thangavelu
Publisher : CRC Press
Page : 591 pages
File Size : 40,8 Mb
Release : 2017-06-26
Category : Computers
ISBN : 9781351720243

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Computational Intelligence Applications in Business Intelligence and Big Data Analytics by Vijayan Sugumaran,Arun Kumar Sangaiah,Arunkumar Thangavelu Pdf

There are a number of books on computational intelligence (CI), but they tend to cover a broad range of CI paradigms and algorithms rather than provide an in-depth exploration in learning and adaptive mechanisms. This book sets its focus on CI based architectures, modeling, case studies and applications in big data analytics, and business intelligence. The intended audiences of this book are scientists, professionals, researchers, and academicians who deal with the new challenges and advances in the specific areas mentioned above. Designers and developers of applications in these areas can learn from other experts and colleagues through this book.

Data Science and Big Data: An Environment of Computational Intelligence

Witold Pedrycz,Shyi-Ming Chen
Data Science and Big Data An Environment of Computational Intelligence Book PDF

Author : Witold Pedrycz,Shyi-Ming Chen
Publisher : Springer
Page : 303 pages
File Size : 50,5 Mb
Release : 2017-03-21
Category : Technology & Engineering
ISBN : 9783319534749

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Data Science and Big Data: An Environment of Computational Intelligence by Witold Pedrycz,Shyi-Ming Chen Pdf

This book presents a comprehensive and up-to-date treatise of a range of methodological and algorithmic issues. It also discusses implementations and case studies, identifies the best design practices, and assesses data analytics business models and practices in industry, health care, administration and business.Data science and big data go hand in hand and constitute a rapidly growing area of research and have attracted the attention of industry and business alike. The area itself has opened up promising new directions of fundamental and applied research and has led to interesting applications, especially those addressing the immediate need to deal with large repositories of data and building tangible, user-centric models of relationships in data. Data is the lifeblood of today’s knowledge-driven economy.Numerous data science models are oriented towards end users and along with the regular requirements for accuracy (which are present in any modeling), come the requirements for ability to process huge and varying data sets as well as robustness, interpretability, and simplicity (transparency). Computational intelligence with its underlying methodologies and tools helps address data analytics needs.The book is of interest to those researchers and practitioners involved in data science, Internet engineering, computational intelligence, management, operations research, and knowledge-based systems.

Data Driven Decision Making using Analytics

Parul Gandhi,Surbhi Bhatia,Kapal Dev
Data Driven Decision Making using Analytics Book PDF

Author : Parul Gandhi,Surbhi Bhatia,Kapal Dev
Publisher : CRC Press
Page : 135 pages
File Size : 55,9 Mb
Release : 2021-12-21
Category : Computers
ISBN : 9781000506495

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Data Driven Decision Making using Analytics by Parul Gandhi,Surbhi Bhatia,Kapal Dev Pdf

This book aims to explain Data Analytics towards decision making in terms of models and algorithms, theoretical concepts, applications, experiments in relevant domains or focused on specific issues. It explores the concepts of database technology, machine learning, knowledge-based system, high performance computing, information retrieval, finding patterns hidden in large datasets and data visualization. Also, it presents various paradigms including pattern mining, clustering, classification, and data analysis. Overall aim is to provide technical solutions in the field of data analytics and data mining. Features: Covers descriptive statistics with respect to predictive analytics and business analytics. Discusses different data analytics platforms for real-time applications. Explain SMART business models. Includes algorithms in data sciences alongwith automated methods and models. Explores varied challenges encountered by researchers and businesses in the realm of real-time analytics. This book aims at researchers and graduate students in data analytics, data sciences, data mining, and signal processing.

Principles of Data Science

Hamid R. Arabnia,Kevin Daimi,Robert Stahlbock,Cristina Soviany,Leonard Heilig,Kai Brüssau
Principles of Data Science Book PDF

Author : Hamid R. Arabnia,Kevin Daimi,Robert Stahlbock,Cristina Soviany,Leonard Heilig,Kai Brüssau
Publisher : Springer
Page : 276 pages
File Size : 44,8 Mb
Release : 2021-07-09
Category : Technology & Engineering
ISBN : 3030439836

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Principles of Data Science by Hamid R. Arabnia,Kevin Daimi,Robert Stahlbock,Cristina Soviany,Leonard Heilig,Kai Brüssau Pdf

This book provides readers with a thorough understanding of various research areas within the field of data science. The book introduces readers to various techniques for data acquisition, extraction, and cleaning, data summarizing and modeling, data analysis and communication techniques, data science tools, deep learning, and various data science applications. Researchers can extract and conclude various future ideas and topics that could result in potential publications or thesis. Furthermore, this book contributes to Data Scientists’ preparation and to enhancing their knowledge of the field. The book provides a rich collection of manuscripts in highly regarded data science topics, edited by professors with long experience in the field of data science. Introduces various techniques, methods, and algorithms adopted by Data Science experts Provides a detailed explanation of data science perceptions, reinforced by practical examples Presents a road map of future trends suitable for innovative data science research and practice

Big Data Analytics: Systems, Algorithms, Applications

C.S.R. Prabhu,Aneesh Sreevallabh Chivukula,Aditya Mogadala,Rohit Ghosh,L.M. Jenila Livingston
Big Data Analytics Systems Algorithms Applications Book PDF

Author : C.S.R. Prabhu,Aneesh Sreevallabh Chivukula,Aditya Mogadala,Rohit Ghosh,L.M. Jenila Livingston
Publisher : Springer Nature
Page : 412 pages
File Size : 45,8 Mb
Release : 2019-10-14
Category : Computers
ISBN : 9789811500947

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Big Data Analytics: Systems, Algorithms, Applications by C.S.R. Prabhu,Aneesh Sreevallabh Chivukula,Aditya Mogadala,Rohit Ghosh,L.M. Jenila Livingston Pdf

This book provides a comprehensive survey of techniques, technologies and applications of Big Data and its analysis. The Big Data phenomenon is increasingly impacting all sectors of business and industry, producing an emerging new information ecosystem. On the applications front, the book offers detailed descriptions of various application areas for Big Data Analytics in the important domains of Social Semantic Web Mining, Banking and Financial Services, Capital Markets, Insurance, Advertisement, Recommendation Systems, Bio-Informatics, the IoT and Fog Computing, before delving into issues of security and privacy. With regard to machine learning techniques, the book presents all the standard algorithms for learning – including supervised, semi-supervised and unsupervised techniques such as clustering and reinforcement learning techniques to perform collective Deep Learning. Multi-layered and nonlinear learning for Big Data are also covered. In turn, the book highlights real-life case studies on successful implementations of Big Data Analytics at large IT companies such as Google, Facebook, LinkedIn and Microsoft. Multi-sectorial case studies on domain-based companies such as Deutsche Bank, the power provider Opower, Delta Airlines and a Chinese City Transportation application represent a valuable addition. Given its comprehensive coverage of Big Data Analytics, the book offers a unique resource for undergraduate and graduate students, researchers, educators and IT professionals alike.

Computational Intelligence for Big Data Analysis

D.P. Acharjya,Satchidananda Dehuri,Sugata Sanyal
Computational Intelligence for Big Data Analysis Book PDF

Author : D.P. Acharjya,Satchidananda Dehuri,Sugata Sanyal
Publisher : Springer
Page : 267 pages
File Size : 43,7 Mb
Release : 2015-04-21
Category : Technology & Engineering
ISBN : 9783319165981

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Computational Intelligence for Big Data Analysis by D.P. Acharjya,Satchidananda Dehuri,Sugata Sanyal Pdf

The work presented in this book is a combination of theoretical advancements of big data analysis, cloud computing, and their potential applications in scientific computing. The theoretical advancements are supported with illustrative examples and its applications in handling real life problems. The applications are mostly undertaken from real life situations. The book discusses major issues pertaining to big data analysis using computational intelligence techniques and some issues of cloud computing. An elaborate bibliography is provided at the end of each chapter. The material in this book includes concepts, figures, graphs, and tables to guide researchers in the area of big data analysis and cloud computing.

Data Analytics

Anthony S. Williams
Data Analytics Book PDF

Author : Anthony S. Williams
Publisher : Anthony S. Williams
Page : 440 pages
File Size : 50,6 Mb
Release : 2024-06-28
Category : Computers
ISBN : 8210379456XXX

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Data Analytics by Anthony S. Williams Pdf

Data Analytics - 7 BOOK BUNDLE!! Book 1: Data Analytics For Beginners In this book you will learn: What is Data Analytics Types of Data Analytics Evolution of Data Analytics Big Data Defined Data Mining Data Visualization Cluster Analysis And of course much more! Book 2: Deep Learning With Keras In this book you will learn: Deep Neural Network Neural Network Elements Keras Models Sequential Model Functional API Model Keras Layers Core Keras Layers Convolutional Keras Layers Recurrent Keras Layers Deep Learning Algorithms Supervised Learning Algorithms Applications of Deep Learning Models Automatic Speech and Image Recognition Natural Language Processing And of course much more! Book 3: Analyzing Data With Power BI In this book you will learn: Basics of data analysis processes Fundamental data analysis algorithms Basic of data and text mining, data visualization, and business intelligence Techniques used for analysing quantitative data Basic data analysis tasks Conceptual, logical, and physical data models Power BI service and data modelling Creating reports and visualizations in Power BI And of course much more! Book 4: Reinforcement Learning With Python In this book you will learn: Types of fundamental machine learning algorithms in comparison to reinforcement learning Essentials of reinforcement learning process Marko decision processes and basic parameters How to integrate reinforcement learning algorithm using OpenAI Gym How to integrate Monte Carlo methods for prediction Monte Carlo tree search And much, much more... Book 5: Artificial Intelligence Python In this book you will learn: Different artificial intelligence approaches and goals How to define AI system Basic AI techniques Reinforcement learning And much, much more... Book 6: Text Analytics With Python In this book you will learn: Text analytics process How to build a corpus and analyze sentiment Named entity extraction with Groningen meaning bank corpus How to train your system Getting started with NLTK How to search syntax and tokenize sentences Automatic text summarization Stemming word and topic modeling with NLTK And much, much more... Book 7: Convolutional Neural Networks In Python In this book you will learn: Architecture of convolutional neural networks Solving computer vision tasks using convolutional neural networks Python and computer vision Automatic image and speech recognition Theano and TenroeFlow image recognition And of course much more! Download this book bundle NOW and SAVE money!!

Foundations of Data Science for Engineering Problem Solving

Parikshit Narendra Mahalle,Gitanjali Rahul Shinde,Priya Dudhale Pise,Jyoti Yogesh Deshmukh
Foundations of Data Science for Engineering Problem Solving Book PDF

Author : Parikshit Narendra Mahalle,Gitanjali Rahul Shinde,Priya Dudhale Pise,Jyoti Yogesh Deshmukh
Publisher : Springer Nature
Page : 125 pages
File Size : 51,5 Mb
Release : 2021-08-21
Category : Technology & Engineering
ISBN : 9789811651601

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Foundations of Data Science for Engineering Problem Solving by Parikshit Narendra Mahalle,Gitanjali Rahul Shinde,Priya Dudhale Pise,Jyoti Yogesh Deshmukh Pdf

This book is one-stop shop which offers essential information one must know and can implement in real-time business expansions to solve engineering problems in various disciplines. It will also help us to make future predictions and decisions using AI algorithms for engineering problems. Machine learning and optimizing techniques provide strong insights into novice users. In the era of big data, there is a need to deal with data science problems in multidisciplinary perspective. In the real world, data comes from various use cases, and there is a need of source specific data science models. Information is drawn from various platforms, channels, and sectors including web-based media, online business locales, medical services studies, and Internet. To understand the trends in the market, data science can take us through various scenarios. It takes help of artificial intelligence and machine learning techniques to design and optimize the algorithms. Big data modelling and visualization techniques of collected data play a vital role in the field of data science. This book targets the researchers from areas of artificial intelligence, machine learning, data science and big data analytics to look for new techniques in business analytics and applications of artificial intelligence in recent businesses.

Applied Machine Learning for Smart Data Analysis

Nilanjan Dey,Sanjeev Wagh,Parikshit N. Mahalle,Mohd. Shafi Pathan
Applied Machine Learning for Smart Data Analysis Book PDF

Author : Nilanjan Dey,Sanjeev Wagh,Parikshit N. Mahalle,Mohd. Shafi Pathan
Publisher : CRC Press
Page : 214 pages
File Size : 45,5 Mb
Release : 2019-05-20
Category : Computers
ISBN : 9780429804564

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Applied Machine Learning for Smart Data Analysis by Nilanjan Dey,Sanjeev Wagh,Parikshit N. Mahalle,Mohd. Shafi Pathan Pdf

The book focuses on how machine learning and the Internet of Things (IoT) has empowered the advancement of information driven arrangements including key concepts and advancements. Ontologies that are used in heterogeneous IoT environments have been discussed including interpretation, context awareness, analyzing various data sources, machine learning algorithms and intelligent services and applications. Further, it includes unsupervised and semi-supervised machine learning techniques with study of semantic analysis and thorough analysis of reviews. Divided into sections such as machine learning, security, IoT and data mining, the concepts are explained with practical implementation including results. Key Features Follows an algorithmic approach for data analysis in machine learning Introduces machine learning methods in applications Address the emerging issues in computing such as deep learning, machine learning, Internet of Things and data analytics Focuses on machine learning techniques namely unsupervised and semi-supervised for unseen and seen data sets Case studies are covered relating to human health, transportation and Internet applications

Machine Learning Paradigms

George A. Tsihrintzis,Dionisios N. Sotiropoulos,Lakhmi C. Jain
Machine Learning Paradigms Book PDF

Author : George A. Tsihrintzis,Dionisios N. Sotiropoulos,Lakhmi C. Jain
Publisher : Springer
Page : 0 pages
File Size : 51,9 Mb
Release : 2018-07-12
Category : Technology & Engineering
ISBN : 3319940295

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Machine Learning Paradigms by George A. Tsihrintzis,Dionisios N. Sotiropoulos,Lakhmi C. Jain Pdf

This book explores some of the emerging scientific and technological areas in which the need for data analytics arises and is likely to play a significant role in the years to come. At the dawn of the 4th Industrial Revolution, data analytics is emerging as a force that drives towards dramatic changes in our daily lives, the workplace and human relationships. Synergies between physical, digital, biological and energy sciences and technologies, brought together by non-traditional data collection and analysis, drive the digital economy at all levels and offer new, previously-unavailable opportunities. The need for data analytics arises in most modern scientific disciplines, including engineering; natural-, computer- and information sciences; economics; business; commerce; environment; healthcare; and life sciences. Coming as the third volume under the general title MACHINE LEARNING PARADIGMS, the book includes an editorial note (Chapter 1) and an additional 12 chapters, and is divided into five parts: (1) Data Analytics in the Medical, Biological and Signal Sciences, (2) Data Analytics in Social Studies and Social Interactions, (3) Data Analytics in Traffic, Computer and Power Networks, (4) Data Analytics for Digital Forensics, and (5) Theoretical Advances and Tools for Data Analytics. This research book is intended for both experts/researchers in the field of data analytics, and readers working in the fields of artificial and computational intelligence as well as computer science in general who wish to learn more about the field of data analytics and its applications. An extensive list of bibliographic references at the end of each chapter guides readers to probe further into the application areas of interest to them.

Data Science and Its Applications

Aakanksha Sharaff,G R Sinha
Data Science and Its Applications Book PDF

Author : Aakanksha Sharaff,G R Sinha
Publisher : CRC Press
Page : 443 pages
File Size : 40,8 Mb
Release : 2021-08-18
Category : Computers
ISBN : 9781000414004

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Data Science and Its Applications by Aakanksha Sharaff,G R Sinha Pdf

The term "data" being mostly used, experimented, analyzed, and researched, "Data Science and its Applications" finds relevance in all domains of research studies including science, engineering, technology, management, mathematics, and many more in wide range of applications such as sentiment analysis, social medial analytics, signal processing, gene analysis, market analysis, healthcare, bioinformatics etc. The book on Data Science and its applications discusses about data science overview, scientific methods, data processing, extraction of meaningful information from data, and insight for developing the concept from different domains, highlighting mathematical and statistical models, operations research, computer programming, machine learning, data visualization, pattern recognition and others. The book also highlights data science implementation and evaluation of performance in several emerging applications such as information retrieval, cognitive science, healthcare, and computer vision. The data analysis covers the role of data science depicting different types of data such as text, image, biomedical signal etc. useful for a wide range of real time applications. The salient features of the book are: Overview, Challenges and Opportunities in Data Science and Real Time Applications Addressing Big Data Issues Useful Machine Learning Methods Disease Detection and Healthcare Applications utilizing Data Science Concepts and Deep Learning Applications in Stock Market, Education, Behavior Analysis, Image Captioning, Gene Analysis and Scene Text Analysis Data Optimization Due to multidisciplinary applications of data science concepts, the book is intended for wide range of readers that include Data Scientists, Big Data Analysists, Research Scholars engaged in Data Science and Machine Learning applications.

Cognitive Computing and Big Data Analytics

Judith S. Hurwitz,Marcia Kaufman,Adrian Bowles
Cognitive Computing and Big Data Analytics Book PDF

Author : Judith S. Hurwitz,Marcia Kaufman,Adrian Bowles
Publisher : John Wiley & Sons
Page : 288 pages
File Size : 48,7 Mb
Release : 2015-02-12
Category : Computers
ISBN : 9781118896631

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Cognitive Computing and Big Data Analytics by Judith S. Hurwitz,Marcia Kaufman,Adrian Bowles Pdf

A comprehensive guide to learning technologies that unlock the value in big data Cognitive Computing provides detailed guidance toward building a new class of systems that learn from experience and derive insights to unlock the value of big data. This book helps technologists understand cognitive computing's underlying technologies, from knowledge representation techniques and natural language processing algorithms to dynamic learning approaches based on accumulated evidence, rather than reprogramming. Detailed case examples from the financial, healthcare, and manufacturing walk readers step-by-step through the design and testing of cognitive systems, and expert perspectives from organizations such as Cleveland Clinic, Memorial Sloan-Kettering, as well as commercial vendors that are creating solutions. These organizations provide insight into the real-world implementation of cognitive computing systems. The IBM Watson cognitive computing platform is described in a detailed chapter because of its significance in helping to define this emerging market. In addition, the book includes implementations of emerging projects from Qualcomm, Hitachi, Google and Amazon. Today's cognitive computing solutions build on established concepts from artificial intelligence, natural language processing, ontologies, and leverage advances in big data management and analytics. They foreshadow an intelligent infrastructure that enables a new generation of customer and context-aware smart applications in all industries. Cognitive Computing is a comprehensive guide to the subject, providing both the theoretical and practical guidance technologists need. Discover how cognitive computing evolved from promise to reality Learn the elements that make up a cognitive computing system Understand the groundbreaking hardware and software technologies behind cognitive computing Learn to evaluate your own application portfolio to find the best candidates for pilot projects Leverage cognitive computing capabilities to transform the organization Cognitive systems are rightly being hailed as the new era of computing. Learn how these technologies enable emerging firms to compete with entrenched giants, and forward-thinking established firms to disrupt their industries. Professionals who currently work with big data and analytics will see how cognitive computing builds on their foundation, and creates new opportunities. Cognitive Computing provides complete guidance to this new level of human-machine interaction.

Practical Machine Learning for Data Analysis Using Python

Abdulhamit Subasi
Practical Machine Learning for Data Analysis Using Python Book PDF

Author : Abdulhamit Subasi
Publisher : Academic Press
Page : 534 pages
File Size : 45,6 Mb
Release : 2020-06-05
Category : Computers
ISBN : 9780128213803

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Practical Machine Learning for Data Analysis Using Python by Abdulhamit Subasi Pdf

Practical Machine Learning for Data Analysis Using Python is a problem solver’s guide for creating real-world intelligent systems. It provides a comprehensive approach with concepts, practices, hands-on examples, and sample code. The book teaches readers the vital skills required to understand and solve different problems with machine learning. It teaches machine learning techniques necessary to become a successful practitioner, through the presentation of real-world case studies in Python machine learning ecosystems. The book also focuses on building a foundation of machine learning knowledge to solve different real-world case studies across various fields, including biomedical signal analysis, healthcare, security, economics, and finance. Moreover, it covers a wide range of machine learning models, including regression, classification, and forecasting. The goal of the book is to help a broad range of readers, including IT professionals, analysts, developers, data scientists, engineers, and graduate students, to solve their own real-world problems. Offers a comprehensive overview of the application of machine learning tools in data analysis across a wide range of subject areas Teaches readers how to apply machine learning techniques to biomedical signals, financial data, and healthcare data Explores important classification and regression algorithms as well as other machine learning techniques Explains how to use Python to handle data extraction, manipulation, and exploration techniques, as well as how to visualize data spread across multiple dimensions and extract useful features

Machine Learning and Big Data Analytics Paradigms: Analysis, Applications and Challenges

Aboul Ella Hassanien,Ashraf Darwish
Machine Learning and Big Data Analytics Paradigms Analysis Applications and Challenges Book PDF

Author : Aboul Ella Hassanien,Ashraf Darwish
Publisher : Springer Nature
Page : 648 pages
File Size : 45,5 Mb
Release : 2020-12-14
Category : Computers
ISBN : 9783030593384

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Machine Learning and Big Data Analytics Paradigms: Analysis, Applications and Challenges by Aboul Ella Hassanien,Ashraf Darwish Pdf

This book is intended to present the state of the art in research on machine learning and big data analytics. The accepted chapters covered many themes including artificial intelligence and data mining applications, machine learning and applications, deep learning technology for big data analytics, and modeling, simulation, and security with big data. It is a valuable resource for researchers in the area of big data analytics and its applications.