data science IEEE PAPER 2022


Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from noisy, structured and unstructured data, and apply knowledge and actionable insights from data across a broad range of application domains.







Surgical data science from concepts toward clinical translation
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Recent developments in data science in general and machine datadriven approaches and clinical applications have been studied in the fields of radiological and clinical data science

VeridicalFlow: a Python package for building trustworthy data science pipelines with PCS
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and trustworthy data science pipelines using the PCS ( data science pipeline to various judgement calls made during modeling. This ensures that arbitrary judgement calls made by data

Data science appositeness in diabetes mellitus diagnosis for healthcare systems of developing nations
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One of the capacious applications of data science could be its use in bioinformatics. With its The authors use various machine learning, deep learning, and data dimensionality

The Art and Practice of Data Science Pipelines
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data science in-the-small, and a collection of 21 mature data science projects from GitHub to understand data science in-the- Our study has led to three representations of data science The main objective of this book is to help readers to understand how this evolving field of data science is going to be useful in forecasting, prediction, estimation and recommendation. The

Detection of Road Traffic Anomalies Based on Computational Data Science
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The novel element in this research was the use of a computational data science approach data science approach was used in this study to characterize anomalies in road travel data .

Key Aspects of Data Science Methodologies, Issues, Challenges and its Applications
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Through the introduction, research methods, data science projects can be improved through a the topics of data science big data methodologies of conducting a data science project,

The Application of Data Science in Public Health
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Wechat that integrates big data and complicated algorithm to fall into the category of data science via which data is collected, although the wielding of data science might lead to some Aim and Scope The series is focused to explore how disruptive technologies are helping in digital transformation and how organizations are changing the way they do business, science and academia to promote the use of data science in in data science machine learning, data security and IoT, air quality analysis models, data hiding in encrypted images,

Team Bojar Applied glycan data science and machine learning
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Glycowork: A Python package for glycan data science and machine learning. Glycobiology,1 Glycowork is an open-source Python package designed for glycan-related data science and

Data Science and Management
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It takes less time for training because small training data are required for NB to estimate the test data . It linearly scales with the number of predictor features and data points. It is applied of the data . This book differs from other books as it tries to associate data science ( data , operational research, actuarial sciences, and data science . Each chapter is created to gain

An Open-Source Active Learning Curriculum for Data Science in Engineering
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data science to engineers. The content in this project has been used to teach a Data Science problems than is typically found in data science materials. This includes analyzing datasets

Data Science Toolkit: An all-in-one python library to help researchers and practitioners in im-plementing data sciencerelated algorithms with less effort
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We re also aiming to expand the Data Science Toolkit by adding more classes and implementations related to the data science field, such as reinforcement learning, unsupervised

The Science of Data Data Science : Perversions and Possibilities in the Anthropocene Through a Spatial Justice Lens
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considered possible before big data and data science hit the scene In other words, statistics and data science and modeling data about statistics and data science in the Anthropocene. This book explored various facets of data science the big data revolution, and EO new ideas in datadriven research, new applications by integrating emerging data science techniques

Evaluating the Impacts of Security-Durability Characteristic: Data Science Perspective
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the data confidential or secret. In practice, to avoid unauthorized disclosure, its about restricting access to data . 2.2 Integrity The I in the CIA triad stands for is data integrity. This is an

Data Science II
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This course will be 100% self-paced, hands-on exercises that will introduce you to the exciting field of Data Science using computers to manipulate and visualize data to gain

Data Science to Examine Emerging Risks in the FinTech Industry
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to assess data under high data science techniques in a financial analysts toolkit offers benefits that complement existing practices, due to their flexible capabilities. While data science is changed the way life science research is carried science research has adapted to become more and more interdisciplinary, which encompasses biology, engineering, and data science

Supporting Responsible Data and Algorithmic Practices in The News Media
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27]) between data science and data journalism [37 explainable methods available in data science and other related areas to propose a responsible data and algorithm practice for

Leveraging Data Analytics as a key sustainability enabler
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that Data and data science should be applied to solve the existential problems we are facing. More and more platforms promote data for and business models, datadriven solutions are The last decade has been characterized by continuing advances in omics experimental assays, including microarrays that have contributed to produce an enormous amount of data . As

Using Machine Learning to Discover Unexpected Patterns in Clinical Data : A Case Study in COVID-19 Sub-cohort Discovery
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Through the methods we develop, we hope to provide clinicians with a data science framework to identify patients who are at a elevated risk of adverse outcomes from their disease and

MEHTA FAMILY SCHOOL OF DATA SCIENCE AND ARTIFICIAL INTELLIGENCE
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MEHTA FAMILY SCHOOL OF DATA SCIENCE AND ARTIFICIAL INTELLIGENCE INDIAN INSTITUTE OF TECHNOLOGY ROORKEE Ethics for Data Science Data Driven for

Improved KNN Imputation for Missing Values in Gene Expression Data
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Abstract: The problem of missing values has long been studied by researchers working in areas of data science and bioinformatics, especially the analysis of gene expression data that

PLAN 672: Urban Data Analytics in R
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predicting using heterogeneous data sets in urban environments. These data sets that are take towards data analysis and telling stories with data . I highly recommend his new book.

Data Carpentry for Biologists: A semester long Data Carpentry course using ecological and other biological examples
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are learning computing to accomplish specific data management and analysis tasks. In Data Carpentry philosophy of focusing on teaching the skills students need using familiar data

M. Sc. COMPUTER SCIENCE PROGRAMME STRUCTURE COURSE CODE
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characteristics of data sets and compare the trivial and big data for various Data storage platforms for large scale data storage, introduction to Big Data streaming platforms for fast dataVarious Data science techniques can be used to identify what affecting what, why its database increases, more people required data visualization tools to process their data

Deep Learning in Life Science : Generative Models Deep Learning in Life Science : Generative Models
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We apply generative models to toy data sets and to the -as methods for learning the data hyperplane. We discuss why series data of patients and anomalies in (medical) image data . data infrastructures and communication systems. The series will have a prominent applied focus on data fundamental research on data science and networking to data engineering and

International Journal of Data and Network Science
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The hyper-competitive market where companies move without distinction of size or sector, means that they must develop strategies aimed at satisfying the needs of their local, national

APPLICATION OF TREE-BASED PIPELINE OPTIMIZATION IN THE FIELD OF BIOMEDICAL SCIENCE
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With the usage of the notable Scikit-Learn AI library for data changes and AI estimations, it for a judicious showing issue, including data course of action and exhibiting estimations and Investment portfolio optimization problem is an important issue and challenge in the investment field. The goal of portfolio optimization problem is to create an efficient portfolio that

International Journal of Data and Network Science
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This study uses the SEM data analysis method with the help of the Amos device. This research uses quantitative research with primary data sources. The data collection technique used

Machine Learning for Scientific Data Analysis
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integration of single-cell data across samples, experiments, and types of measurement has been very recently highlighted as one of the main challenges in single-cell data science .

Simulation and Testing of Deterministic Finite Automata Machine
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Parth Sheth is currently studying BTech in Artificial intelligence and data science at Vishwakarma Arvind Shelke is currently studying BTech in Artificial intelligence and data science at

International Journal of Data and Network Science
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Sustainable learning and education (SLE) is an emerging philosophy of learning that aims to create and propagate sustainable curricula and methods. SLE is designed to make the

The Adoption of Big Data in Selected Information Institutions in Bangladesh: a study
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are, in general, positive in big data adoption. The study also assessed the understanding level of big data tools like big data data science data mining, data engineering, python, IOT, AI

Eye Tracking and Visual Analytics-A Summary
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more advanced data science concepts like machine learning can be the means of choice in order to analyze the recorded eye tracking data either offline, after the recording of the data

Pattern Matching in File System
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String matching algorithms have had a significant impact on computer science and are used to solve a variety of real-world challenges. It aids in We access this data to keep away from

Colloid and Interface Science Communications
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MATLAB code used to process data sets generated and/or analyzed during the current study

SUPPLEMENTARY MATERIAL FOR MS-GWNN: MULTI-SCALE GRAPH WAVELET NEURAL NETWORK FOR BREAST CANCER DIAGNOSIS
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Implementations. To implement the proposed model, we use the Tensorflow platform on an NVIDIA GeForce GTX 1080 Ti GPU. Each GWNN model consists of three graph

Modeling the civil servant discipline in Indonesia: partial least square-structural equation modeling approach
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to civil servant staff the data being used is a questionnaire the model using the data science technique based on the technique and by using data science technique to support the

Exploration Study of Masters Degree Graduates of Sport Science Study Program of Faculty of Sport Science Yogyakarta State University in Job Acquirement
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data collection technique for this research. Questionnaires either in the printed forms or virtual form via Google Form were given to the object of this study. Data to the analyzed data the

Insights from social sciences can help build an eco-surplus culture for conservation policymaking
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Blind faith in data science without an understanding of what data are missing, or how Western monopoly of climate science is creating an eco-deficit culture. Economy, Land Climate

SUPPLEMENTARY MATERIAL FOR JOINT ATTENTION FOR MEDICAL IMAGE SEGMENTATION
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Implementation Details. All models are implemented with TensorFlow on a Tesla V100 GPU. We use cross entropy loss, a mini-batch of 4 and Adam optimizer with weight decay 10− 8 yet for the data sets including Turkish currency data . For that purpose, this study focuses on currency data set, retrieved from the Turkish Central Bank Exchange Rate data repository,

The COVID-19 Pandemic and Mental Health Concerns on Twitter in the United States
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Background. During the COVID-19 pandemic, mental health concerns (such as fear and loneliness) have been actively discussed on social media. We aim to examine mental health Data science is a correctional that communicates to huge quantity of data which is processed, mined and understandable by machines based on statistical methods and data analysis.

Oral Presentation: Computational Thinking: Engaging Students in STEM During the Age of COVID-19
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had both mathematics and computer science elements. Plans to data science and mathematics courses as well as Big Idea micro-projects during theSpring2022semester . The data

WITH MACHINE LEARNING CLASSIFIERS Ismail Olaniyi MURAINA Computer Science Department, School of Science Adeniran Ogunsanya College of
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The data collected was subjected to both content and face validity approaches using experts in the field of health and data science . The reliability index of 0.87 was obtained using

A Comparative Study of Language Use Observed in Publicity of Keihanna City
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This paper investigates how language use of publicity in Science City changes. Specifically, how the change of language use and its background idea of the city construction are related

3rd Eye Tracking in Games and Play Workshop (PLEY 2022)
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Cognitive aspects during interactions Algorithms for processing eye gaze interaction data Data science concepts for gaze interaction data Collaborative play environments using

DevoLearn: Machine Learning Models and Education that Enable Computational Developmental Biology
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organisms, theory-building activities, and data science tutorials submitted by different contributors. It aims to provide users with Data Science tutorials, web-based applications that offer

An AI-Enabled Predictive Analytics Dashboard for Acute Neurosurgical Referrals
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referral data and for predicting future volume without the need for data science expertise. A lack of data science expertise among clinicians, however, limits this type of analysis,

Data System and Data Management in a Federation of HPC/Cloud Centers
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the LEXIS mission of converging the HPC, cloud, and big data worlds, but also drives collaboration of industry, SMEs, and scientific research in the computing and data science sectors.

Performance Prediction for IMDB Movies
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the well-defined and widely used Data Science Predictions Model Methodology which has followed by collecting and preprocessing data . An exploratory data analysis is done then

data science IEEE PAPER 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




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