Machine Learning Models And Algorithms For Big Data Classification
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Machine Learning Models And Algorithms For Big Data Classification
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Author : Shan Suthaharan
language : en
Publisher: Springer
Release Date : 2015-10-20
Machine Learning Models And Algorithms For Big Data Classification written by Shan Suthaharan and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-10-20 with Business & Economics categories.
This book presents machine learning models and algorithms to address big data classification problems. Existing machine learning techniques like the decision tree (a hierarchical approach), random forest (an ensemble hierarchical approach), and deep learning (a layered approach) are highly suitable for the system that can handle such problems. This book helps readers, especially students and newcomers to the field of big data and machine learning, to gain a quick understanding of the techniques and technologies; therefore, the theory, examples, and programs (Matlab and R) presented in this book have been simplified, hardcoded, repeated, or spaced for improvements. They provide vehicles to test and understand the complicated concepts of various topics in the field. It is expected that the readers adopt these programs to experiment with the examples, and then modify or write their own programs toward advancing their knowledge for solving more complex and challenging problems. The presentation format of this book focuses on simplicity, readability, and dependability so that both undergraduate and graduate students as well as new researchers, developers, and practitioners in this field can easily trust and grasp the concepts, and learn them effectively. It has been written to reduce the mathematical complexity and help the vast majority of readers to understand the topics and get interested in the field. This book consists of four parts, with the total of 14 chapters. The first part mainly focuses on the topics that are needed to help analyze and understand data and big data. The second part covers the topics that can explain the systems required for processing big data. The third part presents the topics required to understand and select machine learning techniques to classify big data. Finally, the fourth part concentrates on the topics that explain the scaling-up machine learning, an important solution for modern big data problems.
Proceedings Of The Future Technologies Conference Ftc 2018
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Author : Kohei Arai
language : en
Publisher: Springer
Release Date : 2018-10-17
Proceedings Of The Future Technologies Conference Ftc 2018 written by Kohei Arai and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-17 with Technology & Engineering categories.
The book, presenting the proceedings of the 2018 Future Technologies Conference (FTC 2018), is a remarkable collection of chapters covering a wide range of topics, including, but not limited to computing, electronics, artificial intelligence, robotics, security and communications and their real-world applications. The conference attracted a total of 503 submissions from pioneering researchers, scientists, industrial engineers, and students from all over the world. After a double-blind peer review process, 173 submissions (including 6 poster papers) have been selected to be included in these proceedings. FTC 2018 successfully brought together technology geniuses in one venue to not only present breakthrough research in future technologies but to also promote practicality and applications and an intra- and inter-field exchange of ideas. In the future, computing technologies will play a very important role in the convergence of computing, communication, and all other computational sciences and applications. And as a result it will also influence the future of science, engineering, industry, business, law, politics, culture, and medicine. Providing state-of-the-art intelligent methods and techniques for solving real-world problems, as well as a vision of the future research, this book is a valuable resource for all those interested in this area.
Machine Learning Applications In Industrial Solid Ash
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Author : Chongchong Qi
language : en
Publisher: Elsevier
Release Date : 2023-12-01
Machine Learning Applications In Industrial Solid Ash written by Chongchong Qi and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-01 with Technology & Engineering categories.
Offering the ability to process large or complex datasets, machine learning (ML) holds huge potential to reshape the whole status for solid ash management and recycling. Machine Learning for Solid Ash Management and Recycling is, as far as the author knows, the first published book about ML in solid ash management and recycling. This book highlights fundamental knowledge and recent advances in this topic, offering readers new insight into how these tools can be utilized to enhance their own work. The reference begins with fundamentals in solid ash, covering the status of solid ash generation and management. The book moves on to foundational knowledge on ML in solid ash management, which provides a brief introduction of ML for solid ash applications. The reference then goes on to discuss ML approaches currently used to address problems in solid ash management and recycling, including solid ash generation, clustering analysis, origin identification, reactivity prediction, leaching potential modelling and metal recovery evaluation, etc. Finally, potential future trends and challenges in the field are discussed. - Helps readers increase their existing knowledge on data mining and ML - Teaches how to apply ML techniques that work best in solid ash management and recycling through providing illustrative examples and complex practice solutions - Provides an accessible introduction to the current state and future possibilities for ML in solid ash management and recycling
Data Science Concepts And Techniques With Applications
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Author : Usman Qamar
language : en
Publisher: Springer Nature
Release Date : 2020-06-08
Data Science Concepts And Techniques With Applications written by Usman Qamar and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-08 with Computers categories.
This book comprehensively covers the topic of data science. Data science is an umbrella term that encompasses data analytics, data mining, machine learning, and several other related disciplines. This book synthesizes both fundamental and advanced topics of a research area that has now reached maturity. The chapters of this book are organized into three sections: The first section is an introduction to data science. Starting from the basic concepts, the book will highlight the types of data, its use, its importance and issues that are normally faced in data analytics. Followed by discussion on wide range of applications of data science and widely used techniques in data science. The second section is devoted to the tools and techniques of data science. It consists of data pre-processing, feature selection, classification and clustering concepts as well as an introduction to text mining and opining mining. And finally, the third section of the book focuses on two programming languages commonly used for data science projects i.e. Python and R programming language. Although this book primarily serves as a textbook, it will also appeal to industrial practitioners and researchers due to its focus on applications and references. The book is suitable for both undergraduate and postgraduate students as well as those carrying out research in data science. It can be used as a textbook for undergraduate students in computer science, engineering and mathematics. It can also be accessible to undergraduate students from other areas with the adequate background. The more advanced chapters can be used by postgraduate researchers intending to gather a deeper theoretical understanding.
International Conference On Signal Machines Automation And Algorithm
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Author : Hasmat Malik
language : en
Publisher: Springer Nature
Release Date : 2024-12-18
International Conference On Signal Machines Automation And Algorithm written by Hasmat Malik and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-18 with Computers categories.
This book is a set of best quality peer-reviewed innovative research papers from the International Conference on Signals, Machines, Automation and Algorithm (SIGMAA 2023), held at Shoolini University, India, during 15–16 December 2023 in hybrid mode. This book has originality of work with the innovative ideas regarding artificial intelligence (AI) and its applications in the field of communication, computing, and power technologies.
International Business
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Author : Thomas Lindner
language : en
Publisher: SAGE Publications Limited
Release Date : 2025-03-28
International Business written by Thomas Lindner and has been published by SAGE Publications Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-28 with Business & Economics categories.
Discover a fresh take on International Business with this textbook, which focuses on the key trends of sustainability and digitalization in today′s global business environment. With a balanced approach of theory, practice and research, the authors discuss different types of organizations (distinguishing between MNEs, SMEs and start-ups) and include examples from a range of countries to compare established and emerging markets. This essential text explores contemporary issues and challenges which have impacted international business and examines cross-functional considerations of IB through discussion of finance, HR and supply chain management Learning features include: Mini cases and in-depth case studies, including the US-China Trade War, sustainability as a driver of competitive advantage at Unilever, Starbucks and the Bean Stock program and digitalization and the global value chain. Sustainability and Digitalization themes in each chapter. Open ended exercise questions allow for group discussions or individual study. Thomas Lindner is Professor of International Management at University of Innsbruck. Jonas Puck is Full Professor at the WU Vienna University of Economics and Business and was the founding Head of WU′s Institute for International Business
Practical Statistical Learning And Data Science Methods
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Author : O. Olawale Awe
language : en
Publisher: Springer Nature
Release Date : 2024-12-27
Practical Statistical Learning And Data Science Methods written by O. Olawale Awe and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-27 with Computers categories.
This contributed volume offers practical implementation strategies for statistical learning and data science techniques, with fully peer-reviewed papers that embody insights and experiences gathered within the LISA 2020 Global Network. Through a series of compelling case studies, readers are immersed in practical methodologies, real-world applications, and innovative approaches in statistical learning and data science. Topics covered in this volume span a wide array of applications, including machine learning in health data analysis, deep learning models for precipitation modeling, interpretation techniques for machine learning models in BMI classification for obesity studies, as well as a comparative analysis of sampling methods in machine learning health applications. By addressing the evolving landscape of data analytics in many ways, this volume serves as a valuable resource for practitioners, researchers, and students alike. The LISA 2020 Global Network is dedicated to enhancing statistical and data science capabilities in developing countries through the establishment of collaboration laboratories, also known as “stat labs.” These stat labs function as engines for development, nurturing the next generation of collaborative statisticians and data scientists while providing essential research infrastructure for researchers, data producers, and decision-makers.
Advanced Intelligent Systems For Sustainable Development Ai2sd 2018
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Author : Mostafa Ezziyyani
language : en
Publisher: Springer
Release Date : 2019-03-06
Advanced Intelligent Systems For Sustainable Development Ai2sd 2018 written by Mostafa Ezziyyani and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-06 with Computers categories.
This book includes the outcomes of the International Conference on Advanced Intelligent Systems for Sustainable Development (AI2SD-2018), held in Tangier, Morocco on July 12–14, 2018. Presenting the latest research in the field of computing sciences and information technology, it discusses new challenges and provides valuable insights into the field, the goal being to stimulate debate, and to promote closer interaction and interdisciplinary collaboration between researchers and practitioners. Though chiefly intended for researchers and practitioners in advanced information technology management and networking, the book will also be of interest to those engaged in emerging fields such as data science and analytics, big data, internet of things, smart networked systems, artificial intelligence, expert systems and cloud computing.
Business Intelligence And Big Data
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Author : Celina M. Olszak
language : en
Publisher: CRC Press
Release Date : 2020-11-17
Business Intelligence And Big Data written by Celina M. Olszak and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-17 with Computers categories.
The twenty-first century is a time of intensifying competition and progressive digitization. Individual employees, managers, and entire organizations are under increasing pressure to succeed. The questions facing us today are: What does success mean? Is success a matter of chance and luck or perhaps is success a category that can be planned and properly supported? Business Intelligence and Big Data: Drivers of Organizational Success examines how the success of an organization largely depends on the ability to anticipate and quickly respond to challenges from the market, customers, and other stakeholders. Success is also associated with the potential to process and analyze a variety of information and the means to use modern information and communication technologies (ICTs). Success also requires creative behaviors and organizational cleverness from an organization. The book discusses business intelligence (BI) and Big Data (BD) issues in the context of modern management paradigms and organizational success. It presents a theoretically and empirically grounded investigation into BI and BD application in organizations and examines such issues as: Analysis and interpretation of the essence of BI and BD Decision support Potential areas of BI and BD utilization in organizations Factors determining success with using BI and BD The role of BI and BD in value creation for organizations Identifying barriers and constraints related to BI and BD design and implementation The book presents arguments and evidence confirming that BI and BD may be a trigger for making more effective decisions, improving business processes and business performance, and creating new business. The book proposes a comprehensive framework on how to design and use BI and BD to provide organizational success.
Emerging Ai Applications In Earth Sciences
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Author : Chander Prabha
language : en
Publisher: Springer Nature
Release Date : 2025-08-03
Emerging Ai Applications In Earth Sciences written by Chander Prabha and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-08-03 with Computers categories.
This proposed book provides deeper insights into artificial intelligence techniques and procedures available for earth sciences. This book unveils several applications of metaheuristic approaches (i.e., swarm intelligence and IoT technologies) in collaboration with AI for earth sciences. It presents the science behind smart technologies that reveal the power of artificial intelligence and IoT. These methodologies help to extract meaningful insights from earth sciences big data analytics. These advanced technologies used in earth science practices can remove geographical barriers, locally adaptive, operationally feasible, and economically affordable. The areas can be explored with the aim of digitizing the whole world. Technological advancement also impacts the financial aspect involved in managing the earth sciences. Intelligent AI applications have made significant strides in the field of earth sciences, offering novel solutions to complex challenges, driving impactful research, and revolutionizing data analysis and interpretation. This intersection of artificial intelligence and earth sciences has paved the way for an enhanced understanding of our planet and its various phenomena.