data science 2021
High-Dimensional Similarity Search for Scalable Data Science
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Similarity search is a core operation of many critical data science applications, involving massive collections of highdimensional objects. Similarity search finds objects in a collection close to a given query according to some definition of sameness. Objects can be data series
Interleaving computational and inferential thinking in an undergraduate data science curriculum
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The undergraduate data science curriculum at the University of California, Berkeley is anchored in five new courses that emphasize computational thinking, inferential thinking, and the perspective gained by working on real-world problems. We believe that interleaving
Data Science Technologies in Economics and Finance: A Gentle Walk-In
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This chapter is an introduction to the use of data science technologies in the fields of economics and finance. The recent explosion in computation and information technology in the past decade has made available vast amounts of data in various domains, which has
Development of Online Learning Material for Data Science Programming using 3D puzzles
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In multidimensional data processing, one of the important data structures is a higher-order tensor or a multidimensional array. In general, the processing related to the higher-order tensor is so complicated that we have been developing understanding support tools for it
Do the Hype of the Benefits from Using New Data Science Tools Extend to Forecasting Extremely Volatile Assets
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This chapter first provides an illustration of the benefits of using machine learning for forecasting relative to traditional econometric strategies. We consider the short-term volatility of the Bitcoin market by realized volatility observations. Our analysis highlights the As practitioners, we aim to provide a consolidated introduction of tidy data science along with routine packages for relational data representation and interpretation, with the focus on analytics related to human genetic interactions. We describe three showcases (also made
International Journal of Population Data Science
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Background Disasters such as the COVID-19 pandemic pose an overwhelming demand on resources that cannot always be met by official organisations. Limited resources and human response to crises can lead members of local communities to turn to one another to fulfil
SciNeM: A Scalable Data Science Tool for Heterogeneous Network Mining.
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ABSTRACT Heterogeneous Information Networks (HINs) provide a natural way to represent various relationships between entities of different types, thus they are valuable in many domains. Analysing and extracting knowledge from HINs typically relies on the concept of
A Survey on Data Science Techniques for Predicting Software Defects.
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In recent years, data science has been used extensively to solve several problems and its application has been extended to several domains. This paper summarises the literature on the synergistic use of Software Engineering and Data Science techniques (eg descriptive
Special collections for hot topics in data science : Call for proposals
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There is no denying it: the scope of Patterns is vast. Since our launch in April 20 we have published papers on topics from algorithmic bias to polymer informatics, and from natural language processing to quantum-processor-inspired machine learning. This big
Introduction to Computational Data Science Using ScalaTion
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Data Science relies on having large amounts of quality data. Collecting data and handling data quality issues are of utmost importance. Without support from a system or framework, this can be very time-consuming and error-prone. This chapter provides a quick overview ofToday we are all witnessing the rapid immersion of society into the digital world. The amount of information is huge, and it is often difficult to distinguish normal news and comments from unreliable information. In this regard, the issue of detecting fake news and countering its
Security of Data Science and Data Science for Security
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Security and data science are two of the fastest developing fields of IT and are being implemented more lately in different applications. In this paper, IN the first section we are going to discuss how security is important for our data, and in the second section, we are
A Platform for Interactive Data Science with Apache Spark for On-premises Infrastructure.
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Various cloud providers offer integrated platforms for interactive development in notebooks for processing and analysis of Big Data on large compute clusters. Such platforms enable users to easily leverage frameworks like Apache Spark as well as to manage clusterKnowledge in engineering sciences is about sharing our ideas of research with others. In engineering, it is exhibited in many ways in that conference is the best way to propose your idea of research and its future scope and it is the best way to add energy to build a strong
Data Science Methods for Declarative Process Mining
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Process mining has recently drawn the attention of a large audience from both research and industry for the analysis of business processes based on execution data. Also, declarative approaches for process modeling and mining which are especially suitable for complex and
International Journal of Population Data Science
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Abstract Introduction Length of Stay (LoS) in Intensive Care Units (ICUs) is an important measure for planning beds capacity during the Covid-19 pandemic. However, as the pandemic progresses and we learn more about the disease, treatment and subsequent LoSToday, it is all about the connected smarter world based on the new emerging technologies and artificial intelligence (AI) for sustainable development. Sustainable development purposes have been designed for meeting the human development goals while
DATA SCIENCE AND ITS RELATION TO BIG DATA AND MACHINE LEARNING
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With the multiple devices owned by us generating a massive amount of data, 2.5 quintillions of data are producing by us every day. Many big companies like Facebook, Instagram, Google, etc., are dealing massive data every second. This led to the creation of terms data
Spatial data science for data driven urban planning: The youth economic discomfort index for Rome
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Today, a consistent segment of the worlds population lives in urban areas, and this proportion will vastly increase in the next decades. Therefore, understanding the key trends in urbanization, likely to unfold over the coming years, is crucial to the implementation of
Data Science in Collaboration, Volume 4. Tsukuba: inext Co., Ltd.
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With the advances of the Internet technologies, online international exchanges are becoming an essential element of teaching and learning communication and collaboration. Some online exchanges known as telecollaboration focus especially on developingIn recent years, data science has been used extensively to solve several problems and its application has been extended to several domains. This paper summarises the literature on the synergistic use of Software Engineering and Data Science techniques (eg descriptive
Information and Communications Technology is Merging Data Science and Advanced Artificial Intelligence Towards the Core of Knowledge Based Society, Part
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The paper analyses the context of evolution of the Data Science (DS) concept, considering the importance of the mutual relations between the evolution of the technology/economy and generally of the society and the ways this is reflected in the peoples minds, as knowledge
Discovering the root cause of impediments using Lean Software Development and Data Science
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Sometimes its hard for professionals to see situations like these as waste, barriers or impediments. The research Im developing in the masters degree program aims to help developers to be more productive by removing unnecessary impediments. I used Data Page 1. 9 III MarchPage 2. International Journal for Research in Applied Science Engineering Technology (IJRASET) ISSN: 2321-9653; IC Value: 45.98; SJ Impact Factor: 7.429 Volume 9 Issue III 2021- Available at www.ijraset.com IJRASET: All Rights are Reserved
A Complete Bibliography of ACM/IMS Transactions on Data Science (TDS)
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Nelson HF Beebe University of Utah Department of Mathematics, 110 LCB 155 S 1400 E RM 233 Salt Lake City, UT 84112-0090 USA E-mail: beebe@math.utah.edu,
DEMYSTIFICATION OF DATASET SHIFT IN THE FIELD OF DATA SCIENCE
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ABSTRACT A change in data distribution is what defines the process of dataset shift. This difference exists between the training and test sets. When building a machine learning algorithm, we use training data to train it in the view that it can yield comparable effects when
On stay at home orders: Using the power of data science for spatial and temporal modeling and visualization of COVID-19
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Coronavirus disease dominated and augmented many aspects of life beginning in early 2020. Related research and data generation developed alongside its spread. We developed a Bayesian spatio-temporal Poisson disease mapping model for estimating real
REGRESSION ANALYSIS IN DATA SCIENCE
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In the statistical literature predicting or learning numeric features is called regression, and it is the subject of research in both machine learning and statistics. This paper reviews the important techniques and algorithms for regression. Regression is important for many
MSc in Data Science and Analytics Dissertation
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Abstract Semantics in the context of Genetic Program (GP) can be understood as the behaviour of a program given a set of inputs and has been well documented in improving performance of GP for a range of complex problems. There have been a variety of different
Clinical Guidelines in Medical Science using Data Science Techniques
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In Medical science the Data mining techniques plays a major role for clinical prediction. Now- a-days the data available in the field of medical sciences is easily accessible. Due to huge amount of data present in this field the prediction of diseases and the health care became
Data Science Time Complexity, and Spacekime Analytics
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❑ In the 18th century, Henry Cavendish used just 23 observations to answer a fundamental question What is the Mass of the Earth He estimated very accurately the mean density of the Earth/H2O (5.483±0.1904 g/cm3)❑ In the 21st century to achieve the same scientific
16. AFRICAS RESPONSES TO COVID-19: AN EARLY DATA SCIENCE VIEW
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COVID-19 is a unique event that has shaken the world. It has disrupted the way we live, how we work, and what we think. Across Africa, the arrival of COVID-19 also drew attention to the continent. We have had to live through grim forecasts of how badly the continent was going
Philosophy, Methodology and Paradigm Shift in Big Data
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He supports proposed the idea of the required dataset by taking this explicitly different influence, such as place, subjectivity, political economy, institutions, rules and systems of thought. Data science is the extraction of knowledge from data
Spatial Data Mining Methods Databases and Statistics Point of Views
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IJAICT India PublicationsSuman Rajest S. et al.(eds.). ICT based Framework for Data ICT based Framework for Data Science and Machine Learning Applications 103 world of big data and machine learning. In this review, first we present the most basic concepts in data science including the structural hierarchy of information and how it is managed. A section is dedicated to discussing topics
Innovative procedures of data preparation to ensure data integrity for crop modelling
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In the first section of the paper, we presented a programming approach to deal with these issues with data science tools, such as R and Python. Programming languages ensured the reproducibility of the process of data preparation
Synthia: multidimensional synthetic data generation in Python
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4.0). Summary Synthetic data be useful in several areas such as healthcare, finance, data science and machine learning (Dahmen Cook; Kamthe et al.; Nowok et al.; Patki et al.). Copula-based
Development of Utilization of Digital Data in JFE Steel
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computers. It was a top level chal- lenge for automation. Recently, installing IoT into pro- duction lines, applications and RD on data science AI and corresponding technologies are being proceeded to utilize big data. In this
Village mentoring and hive learning: The MIT Critical Data experience
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MIMIC-IV and by diffusing them more broadly. The field of health data science would gain tremendously from more interoperability between EHR data sources. Going forward, more shadowing opportunities could be proposed