Data Science and Big Data Analytics is about harnessing the power of data for new insights. The book covers the breadth of activities and methods and tools that Data Scientists use. This guide also helps you understand the many data-mining techniques in use today. Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analytics About This Book Leverage Python's most powerful open-source libraries for deep learning, data wrangling, and data visualization Learn ... This book presents selected papers from the international conference on Data Science & Social Research, held in Naples, Italy in February 2016, and will appeal to researchers in the social sciences working in academia as well as in ... Found inside – Page 246One of the promising areas in the development of operational data analysis tools is the development of specialized visual analytics tools, ... Master the techniques and sophisticated analytics used to construct Spark-based solutions that scale to deliver production-grade data science products About This Book Develop and apply advanced analytical techniques with Spark Learn how to ... This book highlights research and survey articles dedicated to big data techniques for cyber-physical system (CPS), which addresses the close interactions and feedback controls between cyber components and physical components. A basic grasp of data science is recommended in order to fully benefit from this book. This book seeks to promote the exploitation of data science in healthcare systems. This book presents outstanding theoretical and practical findings in data science and associated interdisciplinary areas. Found insideThe body of knowledge essential for data science, and different tools technologies used in data science are also parts of this chapter. "This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience"-- Found insideThe proposed book will discuss various aspects of big data Analytics. It will deliberate upon the tools, technology, applications, use cases and research directions in the field. This open access book covers the use of data science, including advanced machine learning, big data analytics, Semantic Web technologies, natural language processing, social media analysis, time series analysis, among others, for ... Found inside – Page 72Bruno's blog post describes how he has struggled to do cheap data science in ... world's potential data scientists of access to the tools and technologies ... But how can you get started working in a wide-ranging, interdisciplinary field that’s so clouded in hype? 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Found inside – Page 95Analytics tools are the software and Software as a Service (SaaS) technologies that are critical and necessary for collecting, reporting, and analyzing data ... Found inside – Page 305... computer science , information security , and interdisciplinary tools , along with the latest methods and technologies used . Ninety percent of data ... The proposed book will discuss various aspects of big data Analytics. It will deliberate upon the tools, technology, applications, use cases and research directions in the field. Found inside – Page 33consequently were reluctant to apply all this technology. ... Without data science tools, there were various factors adding to the cost like large number of ... The peer-reviewed contributions gathered in this book address methods, software and applications of statistics and data science in the social sciences. Who This Book Is For Startup founders, product managers, higher level managers, and any other non-technical decision makers who are thinking to implement data science in their organization and hire data scientists. Found inside – Page 449Data science algorithms. In order to choose the best data science tools for QVida+ project, it is important to overview algorithms and techniques that are ... This book is helpful for the students, practitioners, researchers as well as industry professional. This book includes an extended version of selected papers presented at the 11th Industry Symposium 2021 held during January 7–10, 2021. Topics and features: Reviews a framework for fast data applications, a technique for complex event processing, and a selection of agglomerative approaches for partitioning of networks Discusses a big data approach to identifying minimum ... 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