Download or read book Artificial Intelligence for Big Data written by Anand Deshpande and published by Packt Publishing Ltd. This book was released on 2018-05-22 with total page 371 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build next-generation Artificial Intelligence systems with Java Key Features Implement AI techniques to build smart applications using Deeplearning4j Perform big data analytics to derive quality insights using Spark MLlib Create self-learning systems using neural networks, NLP, and reinforcement learning Book Description In this age of big data, companies have larger amount of consumer data than ever before, far more than what the current technologies can ever hope to keep up with. However, Artificial Intelligence closes the gap by moving past human limitations in order to analyze data. With the help of Artificial Intelligence for big data, you will learn to use Machine Learning algorithms such as k-means, SVM, RBF, and regression to perform advanced data analysis. You will understand the current status of Machine and Deep Learning techniques to work on Genetic and Neuro-Fuzzy algorithms. In addition, you will explore how to develop Artificial Intelligence algorithms to learn from data, why they are necessary, and how they can help solve real-world problems. By the end of this book, you'll have learned how to implement various Artificial Intelligence algorithms for your big data systems and integrate them into your product offerings such as reinforcement learning, natural language processing, image recognition, genetic algorithms, and fuzzy logic systems. What you will learn Manage Artificial Intelligence techniques for big data with Java Build smart systems to analyze data for enhanced customer experience Learn to use Artificial Intelligence frameworks for big data Understand complex problems with algorithms and Neuro-Fuzzy systems Design stratagems to leverage data using Machine Learning process Apply Deep Learning techniques to prepare data for modeling Construct models that learn from data using open source tools Analyze big data problems using scalable Machine Learning algorithms Who this book is for This book is for you if you are a data scientist, big data professional, or novice who has basic knowledge of big data and wish to get proficiency in Artificial Intelligence techniques for big data. Some competence in mathematics is an added advantage in the field of elementary linear algebra and calculus.

Download or read book AI and Big Data s Potential for Disruptive Innovation written by Strydom, Moses and published by IGI Global. This book was released on 2019-09-27 with total page 427 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big data and artificial intelligence (AI) are at the forefront of technological advances that represent a potential transformational mega-trend—a new multipolar and innovative disruption. These technologies, and their associated management paradigm, are already rapidly impacting many industries and occupations, but in some sectors, the change is just beginning. Innovating ahead of emerging technologies is the new imperative for any organization that aspires to succeed in the next decade. Faced with the power of this AI movement, it is imperative to understand the dynamics and new codes required by the disruption and to adapt accordingly. AI and Big Data’s Potential for Disruptive Innovation provides emerging research exploring the theoretical and practical aspects of successfully implementing new and innovative technologies in a variety of sectors including business, transportation, and healthcare. Featuring coverage on a broad range of topics such as semantic mapping, ethics in AI, and big data governance, this book is ideally designed for IT specialists, industry professionals, managers, executives, researchers, scientists, and engineers seeking current research on the production of new and innovative mechanization and its disruptions.

Download or read book Machine Learning for Big Data Analysis written by Siddhartha Bhattacharyya and published by Walter de Gruyter GmbH & Co KG. This book was released on 2018-12-17 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume comprises six well-versed contributed chapters devoted to report the latest fi ndings on the applications of machine learning for big data analytics. Big data is a term for data sets that are so large or complex that traditional data processing application software is inadequate to deal with them. The possible challenges in this direction include capture, storage, analysis, data curation, search, sharing, transfer, visualization, querying, updating and information privacy. Big data analytics is the process of examining large and varied data sets - i.e., big data - to uncover hidden patterns, unknown correlations, market trends, customer preferences and other useful information that can help organizations make more-informed business decisions. This volume is intended to be used as a reference by undergraduate and post graduate students of the disciplines of computer science, electronics and telecommunication, information science and electrical engineering. THE SERIES: FRONTIERS IN COMPUTATIONAL INTELLIGENCE The series Frontiers In Computational Intelligence is envisioned to provide comprehensive coverage and understanding of cutting edge research in computational intelligence. It intends to augment the scholarly discourse on all topics relating to the advances in artifi cial life and machine learning in the form of metaheuristics, approximate reasoning, and robotics. Latest research fi ndings are coupled with applications to varied domains of engineering and computer sciences. This field is steadily growing especially with the advent of novel machine learning algorithms being applied to different domains of engineering and technology. The series brings together leading researchers that intend to continue to advance the fi eld and create a broad knowledge about the most recent research.

Download or read book Artificial Intelligence and Big Data Analytics for Smart Healthcare written by Miltiadis Lytras and published by Academic Press. This book was released on 2021-10-22 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence and Big Data Analytics for Smart Healthcare serves as a key reference for practitioners and experts involved in healthcare as they strive to enhance the value added of healthcare and develop more sustainable healthcare systems. It brings together insights from emerging sophisticated information and communication technologies such as big data analytics, artificial intelligence, machine learning, data science, medical intelligence, and, by dwelling on their current and prospective applications, highlights managerial and policymaking challenges they may generate. The book is split into five sections: big data infrastructure, framework and design for smart healthcare; signal processing techniques for smart healthcare applications; business analytics (descriptive, diagnostic, predictive and prescriptive) for smart healthcare; emerging tools and techniques for smart healthcare; and challenges (security, privacy, and policy) in big data for smart healthcare. The content is carefully developed to be understandable to different members of healthcare chain to leverage collaborations with researchers and industry. - Presents a holistic discussion on the new landscape of data driven medical technologies including Big Data, Analytics, Artificial Intelligence, Machine Learning, and Precision Medicine - Discusses such technologies with case study driven approach with reference to real world application and systems, to make easier the understanding to the reader not familiar with them - Encompasses an international collaboration perspective, providing understandable knowledge to professionals involved with healthcare to leverage productive partnerships with technology developers

Download or read book Science for Policy Handbook written by Vladimir Sucha and published by Elsevier. This book was released on 2020-07-29 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: Science for Policy Handbook provides advice on how to bring science to the attention of policymakers. This resource is dedicated to researchers and research organizations aiming to achieve policy impacts. The book includes lessons learned along the way, advice on new skills, practices for individual researchers, elements necessary for institutional change, and knowledge areas and processes in which to invest. It puts co-creation at the centre of Science for Policy 2.0, a more integrated model of knowledge-policy relationship. Covers the vital area of science for policymaking Includes contributions from leading practitioners from the Joint Research Centre/European Commission Provides key skills based on the science-policy interface needed for effective evidence-informed policymaking Presents processes of knowledge production relevant for a more holistic science-policy relationship, along with the types of knowledge that are useful in policymaking

Download or read book Big Data Big Design written by Helen Armstrong and published by Chronicle Books. This book was released on 2021-11-04 with total page 177 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big Data, Big Design provides designers with the tools they need to harness the potential of machine learning and put it to use for good through thoughtful, human-centered, intentional design. Enter the world of Machine Learning (ML) and Artificial Intelligence (AI) through a design lens in this thoughtful handbook of practical skills, technical knowledge, interviews, essays, and theory, written specifically for designers. Gain an understanding of the design opportunities and design biases that arise when using predictive algorithms. Learn how to place design principles and cultural context at the heart of AI and ML through real-life case studies and examples. This portable, accessible guide will give beginners and more advanced AI and ML users the confidence to make reasoned, thoughtful decisions when implementing ML design solutions.

Download or read book Demystifying Big Data and Machine Learning for Healthcare written by Prashant Natarajan and published by CRC Press. This book was released on 2017-02-15 with total page 227 pages. Available in PDF, EPUB and Kindle. Book excerpt: Healthcare transformation requires us to continually look at new and better ways to manage insights – both within and outside the organization today. Increasingly, the ability to glean and operationalize new insights efficiently as a byproduct of an organization’s day-to-day operations is becoming vital to hospitals and health systems ability to survive and prosper. One of the long-standing challenges in healthcare informatics has been the ability to deal with the sheer variety and volume of disparate healthcare data and the increasing need to derive veracity and value out of it. Demystifying Big Data and Machine Learning for Healthcare investigates how healthcare organizations can leverage this tapestry of big data to discover new business value, use cases, and knowledge as well as how big data can be woven into pre-existing business intelligence and analytics efforts. This book focuses on teaching you how to: Develop skills needed to identify and demolish big-data myths Become an expert in separating hype from reality Understand the V’s that matter in healthcare and why Harmonize the 4 C’s across little and big data Choose data fi delity over data quality Learn how to apply the NRF Framework Master applied machine learning for healthcare Conduct a guided tour of learning algorithms Recognize and be prepared for the future of artificial intelligence in healthcare via best practices, feedback loops, and contextually intelligent agents (CIAs) The variety of data in healthcare spans multiple business workflows, formats (structured, un-, and semi-structured), integration at point of care/need, and integration with existing knowledge. In order to deal with these realities, the authors propose new approaches to creating a knowledge-driven learning organization-based on new and existing strategies, methods and technologies. This book will address the long-standing challenges in healthcare informatics and provide pragmatic recommendations on how to deal with them.

Download or read book Big Data Analytics and Intelligence written by Poonam Tanwar and published by Emerald Group Publishing. This book was released on 2020-09-30 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big Data Analytics and Intelligence is essential reading for researchers and experts working in the fields of health care, data science, analytics, the internet of things, and information retrieval.

Download or read book E Business written by Robert M.X. Wu and published by BoD – Books on Demand. This book was released on 2021-05-19 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides the latest viewpoints of scientific research in the field of e-business. It is organized into three sections: “Higher Education and Digital Economy Development”, “Artificial Intelligence in E-Business”, and “Business Intelligence Applications”. Chapters focus on China’s higher education in e-commerce, digital economy development, natural language processing applications in business, Information Technology Governance, Risk and Compliance (IT GRC), business intelligence, and more.

Download or read book Big Data written by Viktor Mayer-Schönberger and published by Houghton Mifflin Harcourt. This book was released on 2013 with total page 257 pages. Available in PDF, EPUB and Kindle. Book excerpt: A exploration of the latest trend in technology and the impact it will have on the economy, science, and society at large.

Download or read book Big Data in Practice written by Bernard Marr and published by John Wiley & Sons. This book was released on 2016-03-22 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: The best-selling author of Big Data is back, this time with a unique and in-depth insight into how specific companies use big data. Big data is on the tip of everyone's tongue. Everyone understands its power and importance, but many fail to grasp the actionable steps and resources required to utilise it effectively. This book fills the knowledge gap by showing how major companies are using big data every day, from an up-close, on-the-ground perspective. From technology, media and retail, to sport teams, government agencies and financial institutions, learn the actual strategies and processes being used to learn about customers, improve manufacturing, spur innovation, improve safety and so much more. Organised for easy dip-in navigation, each chapter follows the same structure to give you the information you need quickly. For each company profiled, learn what data was used, what problem it solved and the processes put it place to make it practical, as well as the technical details, challenges and lessons learned from each unique scenario. Learn how predictive analytics helps Amazon, Target, John Deere and Apple understand their customers Discover how big data is behind the success of Walmart, LinkedIn, Microsoft and more Learn how big data is changing medicine, law enforcement, hospitality, fashion, science and banking Develop your own big data strategy by accessing additional reading materials at the end of each chapter

Download or read book Big Data Technologies and Applications written by Borko Furht and published by Springer. This book was released on 2016-09-16 with total page 405 pages. Available in PDF, EPUB and Kindle. Book excerpt: The objective of this book is to introduce the basic concepts of big data computing and then to describe the total solution of big data problems using HPCC, an open-source computing platform. The book comprises 15 chapters broken into three parts. The first part, Big Data Technologies, includes introductions to big data concepts and techniques; big data analytics; and visualization and learning techniques. The second part, LexisNexis Risk Solution to Big Data, focuses on specific technologies and techniques developed at LexisNexis to solve critical problems that use big data analytics. It covers the open source High Performance Computing Cluster (HPCC Systems®) platform and its architecture, as well as parallel data languages ECL and KEL, developed to effectively solve big data problems. The third part, Big Data Applications, describes various data intensive applications solved on HPCC Systems. It includes applications such as cyber security, social network analytics including fraud, Ebola spread modeling using big data analytics, unsupervised learning, and image classification. The book is intended for a wide variety of people including researchers, scientists, programmers, engineers, designers, developers, educators, and students. This book can also be beneficial for business managers, entrepreneurs, and investors.

Download or read book Cognitive Analytics Concepts Methodologies Tools and Applications written by Management Association, Information Resources and published by IGI Global. This book was released on 2020-03-06 with total page 1961 pages. Available in PDF, EPUB and Kindle. Book excerpt: Due to the growing use of web applications and communication devices, the use of data has increased throughout various industries, including business and healthcare. It is necessary to develop specific software programs that can analyze and interpret large amounts of data quickly in order to ensure adequate usage and predictive results. Cognitive Analytics: Concepts, Methodologies, Tools, and Applications provides emerging perspectives on the theoretical and practical aspects of data analysis tools and techniques. It also examines the incorporation of pattern management as well as decision-making and prediction processes through the use of data management and analysis. Highlighting a range of topics such as natural language processing, big data, and pattern recognition, this multi-volume book is ideally designed for information technology professionals, software developers, data analysts, graduate-level students, researchers, computer engineers, software engineers, IT specialists, and academicians.

Download or read book Advances in Artificial Intelligence Big Data and Algorithms written by G. Grigoras and published by IOS Press. This book was released on 2023-12-19 with total page 1224 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computers and automation have revolutionized the lives of most people in the last two decades, and terminology such as algorithms, big data and artificial intelligence have become part of our everyday discourse. This book presents the proceedings of CAIBDA 2023, the 3rd International Conference on Artificial Intelligence, Big Data and Algorithms, held from 16 - 18 June 2023 as a hybrid conference in Zhengzhou, China. The conference provided a platform for some 200 participants to discuss the theoretical and computational aspects of research in artificial intelligence, big data and algorithms, reviewing the present status and future perspectives of the field. A total of 362 submissions were received for the conference, of which 148 were accepted following a thorough double-blind peer review. Topics covered at the conference included artificial intelligence tools and applications; intelligent estimation and classification; representation formats for multimedia big data; high-performance computing; and mathematical and computer modeling, among others. The book provides a comprehensive overview of this fascinating field, exploring future scenarios and highlighting areas where new ideas have emerged over recent years. It will be of interest to all those whose work involves artificial intelligence, big data and algorithms.

Download or read book Think Bigger written by Mark Van Rijmenam and published by AMACOM. This book was released on 2014-04-03 with total page 317 pages. Available in PDF, EPUB and Kindle. Book excerpt: Offering real-world insight and explanations, this book provides a roadmap for organizations looking to develop a profitable big data strategy and reveals why it's not something they can leave to the I.T. department. Big data--the enormous amount of data that is created as virtually every movement, transaction, and choice we make becomes digitized--is revolutionizing business. Sharing best practices from companies that have implemented a big data strategy including Walmart, InterContinental Hotel Group, Walt Disney, and Shell, this helpful resource covers the most important big data trends affecting organizations, as well as key technologies like Hadoop and MapReduce, and several crucial types of analyses. In Think Bigger, you will find guidance on topics such as: how to ensure security, respecting the privacy rights of consumers, and how big data is impacting specific industries--and where opportunities can be found. Big data is changing the way businesses--and even governments--are operated and managed. Think Bigger is an essential resource for anyone who wants to ensure that their company isn't left in the dust.

Download or read book Artificial Intelligence for COVID 19 written by Diego Oliva and published by Springer Nature. This book was released on 2021-07-19 with total page 594 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a compilation of the most recent implementation of artificial intelligence methods for solving different problems generated by the COVID-19. The problems addressed came from different fields and not only from medicine. The information contained in the book explores different areas of machine and deep learning, advanced image processing, computational intelligence, IoT, robotics and automation, optimization, mathematical modeling, neural networks, information technology, big data, data processing, data mining, and likewise. Moreover, the chapters include the theory and methodologies used to provide an overview of applying these tools to the useful contribution to help to face the emerging disaster. The book is primarily intended for researchers, decision makers, practitioners, and readers interested in these subject matters. The book is useful also as rich case studies and project proposals for postgraduate courses in those specializations.

Download or read book Big Data Meets Survey Science written by Craig A. Hill and published by John Wiley & Sons. This book was released on 2020-09-29 with total page 784 pages. Available in PDF, EPUB and Kindle. Book excerpt: Offers a clear view of the utility and place for survey data within the broader Big Data ecosystem This book presents a collection of snapshots from two sides of the Big Data perspective. It assembles an array of tangible tools, methods, and approaches that illustrate how Big Data sources and methods are being used in the survey and social sciences to improve official statistics and estimates for human populations. It also provides examples of how survey data are being used to evaluate and improve the quality of insights derived from Big Data. Big Data Meets Survey Science: A Collection of Innovative Methods shows how survey data and Big Data are used together for the benefit of one or more sources of data, with numerous chapters providing consistent illustrations and examples of survey data enriching the evaluation of Big Data sources. Examples of how machine learning, data mining, and other data science techniques are inserted into virtually every stage of the survey lifecycle are presented. Topics covered include: Total Error Frameworks for Found Data; Performance and Sensitivities of Home Detection on Mobile Phone Data; Assessing Community Wellbeing Using Google Street View and Satellite Imagery; Using Surveys to Build and Assess RBS Religious Flag; and more. Presents groundbreaking survey methods being utilized today in the field of Big Data Explores how machine learning methods can be applied to the design, collection, and analysis of social science data Filled with examples and illustrations that show how survey data benefits Big Data evaluation Covers methods and applications used in combining Big Data with survey statistics Examines regulations as well as ethical and privacy issues Big Data Meets Survey Science: A Collection of Innovative Methods is an excellent book for both the survey and social science communities as they learn to capitalize on this new revolution. It will also appeal to the broader data and computer science communities looking for new areas of application for emerging methods and data sources.