Deep Learning Techniques and Optimization Strategies in Big Data Analytics - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Deep Learning Techniques and Optimization Strategies in Big Data Analytics write by J. Joshua Thomas. This book was released on 2019-11. Deep Learning Techniques and Optimization Strategies in Big Data Analytics available in PDF, EPUB and Kindle. "This book examines the application of artificial intelligence in machine learning, data mining in unstructured data sets or databases, web mining, and information retrieval"--
Deep Learning Techniques and Optimization Strategies in Big Data Analytics
Deep Learning Techniques and Optimization Strategies in Big Data Analytics - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Deep Learning Techniques and Optimization Strategies in Big Data Analytics write by Thomas, J. Joshua. This book was released on 2019-11-29. Deep Learning Techniques and Optimization Strategies in Big Data Analytics available in PDF, EPUB and Kindle. Many approaches have sprouted from artificial intelligence (AI) and produced major breakthroughs in the computer science and engineering industries. Deep learning is a method that is transforming the world of data and analytics. Optimization of this new approach is still unclear, however, and there’s a need for research on the various applications and techniques of deep learning in the field of computing. Deep Learning Techniques and Optimization Strategies in Big Data Analytics is a collection of innovative research on the methods and applications of deep learning strategies in the fields of computer science and information systems. While highlighting topics including data integration, computational modeling, and scheduling systems, this book is ideally designed for engineers, IT specialists, data analysts, data scientists, engineers, researchers, academicians, and students seeking current research on deep learning methods and its application in the digital industry.
Deep Learning in Data Analytics
Deep Learning in Data Analytics - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Deep Learning in Data Analytics write by Debi Prasanna Acharjya. This book was released on 2021-08-11. Deep Learning in Data Analytics available in PDF, EPUB and Kindle. This book comprises theoretical foundations to deep learning, machine learning and computing system, deep learning algorithms, and various deep learning applications. The book discusses significant issues relating to deep learning in data analytics. Further in-depth reading can be done from the detailed bibliography presented at the end of each chapter. Besides, this book's material includes concepts, algorithms, figures, graphs, and tables in guiding researchers through deep learning in data science and its applications for society. Deep learning approaches prevent loss of information and hence enhance the performance of data analysis and learning techniques. It brings up many research issues in the industry and research community to capture and access data effectively. The book provides the conceptual basis of deep learning required to achieve in-depth knowledge in computer and data science. It has been done to make the book more flexible and to stimulate further interest in topics. All these help researchers motivate towards learning and implementing the concepts in real-life applications.
Deep Learning: Convergence to Big Data Analytics
Deep Learning: Convergence to Big Data Analytics - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Deep Learning: Convergence to Big Data Analytics write by Murad Khan. This book was released on 2018-12-30. Deep Learning: Convergence to Big Data Analytics available in PDF, EPUB and Kindle. This book presents deep learning techniques, concepts, and algorithms to classify and analyze big data. Further, it offers an introductory level understanding of the new programming languages and tools used to analyze big data in real-time, such as Hadoop, SPARK, and GRAPHX. Big data analytics using traditional techniques face various challenges, such as fast, accurate and efficient processing of big data in real-time. In addition, the Internet of Things is progressively increasing in various fields, like smart cities, smart homes, and e-health. As the enormous number of connected devices generate huge amounts of data every day, we need sophisticated algorithms to deal, organize, and classify this data in less processing time and space. Similarly, existing techniques and algorithms for deep learning in big data field have several advantages thanks to the two main branches of the deep learning, i.e. convolution and deep belief networks. This book offers insights into these techniques and applications based on these two types of deep learning. Further, it helps students, researchers, and newcomers understand big data analytics based on deep learning approaches. It also discusses various machine learning techniques in concatenation with the deep learning paradigm to support high-end data processing, data classifications, and real-time data processing issues. The classification and presentation are kept quite simple to help the readers and students grasp the basics concepts of various deep learning paradigms and frameworks. It mainly focuses on theory rather than the mathematical background of the deep learning concepts. The book consists of 5 chapters, beginning with an introductory explanation of big data and deep learning techniques, followed by integration of big data and deep learning techniques and lastly the future directions.
Machine Learning and Big Data Analytics Paradigms: Analysis, Applications and Challenges
Machine Learning and Big Data Analytics Paradigms: Analysis, Applications and Challenges - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Machine Learning and Big Data Analytics Paradigms: Analysis, Applications and Challenges write by Aboul Ella Hassanien. This book was released on 2020-12-14. Machine Learning and Big Data Analytics Paradigms: Analysis, Applications and Challenges available in PDF, EPUB and Kindle. 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.
