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contribution to the area of big data and visual analytics. This book is a valuable resource for researchers and professionals working in the area;
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considered an essential part of data science methodology and practices. It then describes the general principles underlying the visual analytics;
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considered an essential part of data science methodology and practices. It then describes the general principles underlying the visual analytics;
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This book discusses semantic interaction, a user interaction methodology for visual analytic applications that more closely couples the;
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This book discusses semantic interaction, a user interaction methodology for visual analytic applications that more closely couples the;
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, Machine Learning, and Big Data - That You Don't Data Science for Business: Predictive Modeling, Data Mining, Data Analytics, Data Warehousing;
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At the intersection of computer science and healthcare, data analytics has emerged as a promising tool for solving problems across many;
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A practical guide for anyone who aspires to become data analytics-savvy Data analytics has become central to the operation of most;
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Standard tutorial-based approach. Getting Started with Greenplum for Big Data Analytics is great for data scientists and data analysts with;
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control towers. Basic methods in the areas of visual, descriptive, predictive, and prescriptive analytics and Big Data are introduced;
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Big data consists of data sets that are too large and complex for traditional data processing and data management applications. Therefore;
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Big Data Analytics Methods unveils secrets to advanced analytics techniques ranging from machine learning, random forest classifiers;
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This book provides detailed descriptions of big data solutions for activity detection and forecasting of very large numbers of moving;
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This book provides detailed descriptions of big data solutions for activity detection and forecasting of very large numbers of moving;
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Public Policy Analytics: Code & Context for Data Science in Government teaches readers how to address complex public policy problems with;
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Public Policy Analytics: Code & Context for Data Science in Government teaches readers how to address complex public policy problems with;
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learning, and fuzzy logic, this book is ideally designed for students, government officials, data scientists, managers, consultants, analysts, IT;
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, this chapter attempts to provide an initial set of guidelines for the creation of the visual representation, including pitfalls and areas where;
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in health sciences and biomedical data. The book is useful for those working with big data analytics in biomedical research, medical industries, and;
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intelligence for making better healthcare decisions. Identifying patterns and correlations contained in complex health data, analytics has applications;
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them to gain better insight from this data in order to improve healthcare outcomes. This book is a complete overview of machine learning for;
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Text As Data: Combining qualitative and quantitative algorithms within the SAS system for accurate, effective and understandable text;
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Demystifying Big Data, Machine Learning, and Deep Learning for Healthcare Analytics presents the changing world of data utilization;
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The definitive guide for statisticians and data scientists who understand the advantages of becoming proficient in both R and Python;
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This book, Data Science: What the Best Data Scientists Know About Data Analytics, Data Mining, Statistics, Machine Learning, and Big Data;
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As technology continues to advance, it is critical for businesses to implement systems that can support the transformation of data into;
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for decision-making. Note that structured data can be easily analyzed by efficient (available) business intelligence tools, while most of the;
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