data science 2018


MLxtend: Providing machine learning and data science utilities and extensions to Pythons scientific computing stack
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MLxtend is a library that implements a variety of core algorithms and utilities for machine learning and data mining. The primary goal of MLxtend is to make commonly used tools accessible to researchers in academia and data scientists in industries focussing on

Data Science Challenges in Gravitational Wave Astronomy
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Toward a System Building Agenda for Data Integration (and Data Science ).
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We argue that the data integration (DI) community should devote far more effort to building systems, in order to truly advance the field. We discuss the limitations of current DI systems, and point out that there is already an existing popular DI system out there, which is PyData In the modern information age, data and decisions are more strongly linked than ever before. The recent emergence of data science as an interdisciplinary field that aims to distil insights from data and that informs data-driven decision-making bears witness to the

Learning health systems need to bridge thetwo cultures of clinical informatics and data science
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Background UK health research policy and plans for population health management are predicated upon transformative knowledge discovery from operational Big Data. Learning health systems require not only data, but feedback loops of knowledge into changed

Semantic Representation of Data Science Programs.
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Your computer through which you are, in all likelihood, reading this paper is continuously, efficiently, and reliably executing computer programs, but does it really understand them Not in any meaningful sense. That burden falls upon human knowledge

Microservice Architectures for Data Science Applications
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Page 1. Microservice Architectures for Data Science Applications Data Science Symposium,

BBVA Fuels Digital Transformation Progress with a Data Science Center of Excellence
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a global financial group with 691 billion in total assets, headquartered in Madrid and operating in more than thirty countries. BBVAs 132,000 employees served 72 million customers in the areas of Conference on Soft Methods in Probability and Statistics (SMPS 2018), which was held in conjunction with the 5th International Conference on Belief Functions (BELIEF 2018) on 17 The series of biannual International Conference

Data Science , Sentiment Analysis and the Impact of Free Speech on Social Media
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Data Science , has evolved from the seemingly sort of thing mysteriously practised by mathematicians, statisticians and economist, with their extent of deep organic knowledge to fathom its power. Today, data isnta mystery anymore. Data Science is endemic to modern

A Review on Data Science Technologies
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Data science is secure in with managing huge nature of information to extract significant and coherent outcomes/conclusions/designs. It is a recently rising field that incorporates various exercises, for example, data mining and information investigation. It utilizes procedures

Big Data: The Next Era of Informatics and Data Science in Medical Imaging: A Literature Review
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Big data is an evolving topic of research in recent years and provides much promise in all fields, including medicine and radiology. The purpose of this literature review is to define big data, and discuss its relevance to medical imaging informatics. Relevant imaging informatics

Algorithmic Government: Automating Public Services and Supporting Civil Servants in using Data Science Technologies
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The data science technologies of artificial intelligence (AI), Internet of Things (IoT), big data and behavioral/predictive analytics, and blockchain are poised to revolutionize government and create a new generation of GovTech start-ups. The impact from the smartificationof We live in a data-driven society. The search for innovative solutions and competitive advantage has led to digital revolution where a huge amount of data is produced every day. Todays organizations are facing new challenges in processing and analyzing this massive

Big Data Science Training Program at a Minority Serving Institution: Processes and Initial Outcomes
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Big Data refers to data that are so large and complex, making it difficult or impossible to manage with traditional computing/software and hardware . The volume of electronic data worldwide, just in the healthcare field, is overwhelming with an The series Advances in Intelligent Systems and Computing contains publications on theory, applications, and design methods of Intelligent Systems and Intelligent Computing. Virtually all disciplines such as engineering, natural sciences, computer and information science The increased availability of vast and highly varied amounts of data from learners, teachers, learning environments, and administrative systems within educational settings is overwhelming. The focus of this chapter is on how data with a large number of records, of

Environmental data science
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Physics Set-up Sources s: multiple, spiky; Gaussian mixture Background b: smooth; Gaussian Markov random field, wind covariate Plume A: Gaussian Parameters Source locations z, widths w and emission rates ρ for mixture of m sources Random field

Value based pricing meets data science : A concept for automated spare part valuation
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Turning data into value is an exciting challenge for Data Science in times of an exponential growing amount of data. Maintenance, Repair and Overhaul companies are facing pricing related decision problems on a daily basis. The industry sits on vast amount of data. Due to

What is Data Science
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Data Science , a new discovery paradigm, is potentially one of the most significant advances of the early 21st century. Originating in scientific discovery, it is being applied to every human endeavor for which there is adequate data. While remarkable successes have been

Data Science for Finite Strain Mechanical Science of Ductile Materials
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A mechanical science of materials based on data science is formulated to predict process- structure-propertyperformance relationships. This general formulation encompasses multiple approaches that have been proposed in the literature to reduce the complexity of

Computational Personalization: Data science methods for personalized health
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In the last decade authoritative scientific journals such as Science (Ng et al., 2009) and the New England journal of Medicine (Hamburg and Collins, 2010), as well as legislative bodies such as the American Food and Drug Administration (FDA) and the European Union (EU)

Data science and healthcare
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Summary The Big Data ecosystem consists of five components:(1) data creation,(2) data collection and management,(3) analysis and information extraction,(4) hypothesis and experiment and (5) decision-making and action. We propose to use data science in which

On Developing Data Science
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Understanding phenomena based on the facts on the data is a touchstone of data science . The power of evidence-based, inductive reasoning distinguishes data science from science. Hence, this chapter argues that, in its initial stages, data science applications and the data

Data Science for Startups
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In 2017, I changed industries and joined a startup company where I was responsible for building up a data science discipline. While we already had a solid data pipeline in place when I joined, we didnt have processes in place for reproducible analysis, scaling up

Data Science in Cyber Security: Network Security Threat Detection
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In this new era of digitalization, cyber-attacks are controlled by creative, intelligent and highly skilled humans. Ongoing synchronization allows an attacker to gradually learn more about the target network, adapt to any defensive measures, and advance the attack over

Skills Requirements of Business Data Analytics and Data Science Jobs: A Comparative Analysis
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Big data analytics is increasingly shaping the way organizations manage their decision- making processes, create new services and products, and gain competitive advantage. The demand for analytics and its applications is driving the expansion of information technology

The Fundamental Principle of Data Science
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