Data science and Machine learning in the Clouds: A Perspective for the Future
As we are fast approaching the beginning of a paradigm shift in the field of science, Data driven science (the so called fourth science paradigm) is going to be the driving force in research and innovation. From medicine to biodiversity and astronomy to geology, all these terms are somehow going to...
Gespeichert in:
Veröffentlicht in: | arXiv.org 2021-09 |
---|---|
1. Verfasser: | |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | |
---|---|
container_issue | |
container_start_page | |
container_title | arXiv.org |
container_volume | |
creator | Hrishav Bakul Barua |
description | As we are fast approaching the beginning of a paradigm shift in the field of science, Data driven science (the so called fourth science paradigm) is going to be the driving force in research and innovation. From medicine to biodiversity and astronomy to geology, all these terms are somehow going to be affected by this paradigm shift. The huge amount of data to be processed under this new paradigm will be a major concern in the future and one will strongly require cloud based services in all the aspects of these computations (from storage to compute and other services). Another aspect will be energy consumption and performance of prediction jobs and tasks within such a scientific paradigm which will change the way one sees computation. Data science has heavily impacted or rather triggered the emergence of Machine Learning, Signal/Image/Video processing related algorithms, Artificial intelligence, Robotics, health informatics, geoinformatics, and many more such areas of interest. Hence, we envisage an era where Data science can deliver its promises with the help of the existing cloud based platforms and services with the addition of new services. In this article, we discuss about data driven science and Machine learning and how they are going to be linked through cloud based services in the future. It also discusses the rise of paradigms like approximate computing, quantum computing and many more in recent times and their applicability in big data processing, data science, analytics, prediction and machine learning in the cloud environments. |
format | Article |
fullrecord | <record><control><sourceid>proquest</sourceid><recordid>TN_cdi_proquest_journals_2569853219</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2569853219</sourcerecordid><originalsourceid>FETCH-proquest_journals_25698532193</originalsourceid><addsrcrecordid>eNqNyk8LgjAYgPERBEn5HV7oLOjmTLuFJV2EDt1lzNecyGb70-cvog_Q6Tn8nhWJKGNZUuaUbkjs3JSmKS0OlHMWkfYsvAAnFWqJIHQPrZCj0ggzCquVfoDS4EeEejahd0c4wQ2tW1B69UIYjP1qE3ywuCPrQcwO41-3ZN9c7vU1Wax5BnS-m0yw-kMd5UVVckaziv13vQH55zzM</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2569853219</pqid></control><display><type>article</type><title>Data science and Machine learning in the Clouds: A Perspective for the Future</title><source>Free E- Journals</source><creator>Hrishav Bakul Barua</creator><creatorcontrib>Hrishav Bakul Barua</creatorcontrib><description>As we are fast approaching the beginning of a paradigm shift in the field of science, Data driven science (the so called fourth science paradigm) is going to be the driving force in research and innovation. From medicine to biodiversity and astronomy to geology, all these terms are somehow going to be affected by this paradigm shift. The huge amount of data to be processed under this new paradigm will be a major concern in the future and one will strongly require cloud based services in all the aspects of these computations (from storage to compute and other services). Another aspect will be energy consumption and performance of prediction jobs and tasks within such a scientific paradigm which will change the way one sees computation. Data science has heavily impacted or rather triggered the emergence of Machine Learning, Signal/Image/Video processing related algorithms, Artificial intelligence, Robotics, health informatics, geoinformatics, and many more such areas of interest. Hence, we envisage an era where Data science can deliver its promises with the help of the existing cloud based platforms and services with the addition of new services. In this article, we discuss about data driven science and Machine learning and how they are going to be linked through cloud based services in the future. It also discusses the rise of paradigms like approximate computing, quantum computing and many more in recent times and their applicability in big data processing, data science, analytics, prediction and machine learning in the cloud environments.</description><identifier>EISSN: 2331-8422</identifier><language>eng</language><publisher>Ithaca: Cornell University Library, arXiv.org</publisher><subject>Algorithms ; Artificial intelligence ; Astronomy ; Biodiversity ; Cloud computing ; Data processing ; Data science ; Energy consumption ; Image processing ; Machine learning ; Quantum computing ; Robotics ; Science ; Signal processing ; Video</subject><ispartof>arXiv.org, 2021-09</ispartof><rights>2021. This work is published under http://arxiv.org/licenses/nonexclusive-distrib/1.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>776,780</link.rule.ids></links><search><creatorcontrib>Hrishav Bakul Barua</creatorcontrib><title>Data science and Machine learning in the Clouds: A Perspective for the Future</title><title>arXiv.org</title><description>As we are fast approaching the beginning of a paradigm shift in the field of science, Data driven science (the so called fourth science paradigm) is going to be the driving force in research and innovation. From medicine to biodiversity and astronomy to geology, all these terms are somehow going to be affected by this paradigm shift. The huge amount of data to be processed under this new paradigm will be a major concern in the future and one will strongly require cloud based services in all the aspects of these computations (from storage to compute and other services). Another aspect will be energy consumption and performance of prediction jobs and tasks within such a scientific paradigm which will change the way one sees computation. Data science has heavily impacted or rather triggered the emergence of Machine Learning, Signal/Image/Video processing related algorithms, Artificial intelligence, Robotics, health informatics, geoinformatics, and many more such areas of interest. Hence, we envisage an era where Data science can deliver its promises with the help of the existing cloud based platforms and services with the addition of new services. In this article, we discuss about data driven science and Machine learning and how they are going to be linked through cloud based services in the future. It also discusses the rise of paradigms like approximate computing, quantum computing and many more in recent times and their applicability in big data processing, data science, analytics, prediction and machine learning in the cloud environments.</description><subject>Algorithms</subject><subject>Artificial intelligence</subject><subject>Astronomy</subject><subject>Biodiversity</subject><subject>Cloud computing</subject><subject>Data processing</subject><subject>Data science</subject><subject>Energy consumption</subject><subject>Image processing</subject><subject>Machine learning</subject><subject>Quantum computing</subject><subject>Robotics</subject><subject>Science</subject><subject>Signal processing</subject><subject>Video</subject><issn>2331-8422</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNqNyk8LgjAYgPERBEn5HV7oLOjmTLuFJV2EDt1lzNecyGb70-cvog_Q6Tn8nhWJKGNZUuaUbkjs3JSmKS0OlHMWkfYsvAAnFWqJIHQPrZCj0ggzCquVfoDS4EeEejahd0c4wQ2tW1B69UIYjP1qE3ywuCPrQcwO41-3ZN9c7vU1Wax5BnS-m0yw-kMd5UVVckaziv13vQH55zzM</recordid><startdate>20210902</startdate><enddate>20210902</enddate><creator>Hrishav Bakul Barua</creator><general>Cornell University Library, arXiv.org</general><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>L6V</scope><scope>M7S</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope></search><sort><creationdate>20210902</creationdate><title>Data science and Machine learning in the Clouds: A Perspective for the Future</title><author>Hrishav Bakul Barua</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-proquest_journals_25698532193</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Algorithms</topic><topic>Artificial intelligence</topic><topic>Astronomy</topic><topic>Biodiversity</topic><topic>Cloud computing</topic><topic>Data processing</topic><topic>Data science</topic><topic>Energy consumption</topic><topic>Image processing</topic><topic>Machine learning</topic><topic>Quantum computing</topic><topic>Robotics</topic><topic>Science</topic><topic>Signal processing</topic><topic>Video</topic><toplevel>online_resources</toplevel><creatorcontrib>Hrishav Bakul Barua</creatorcontrib><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Engineering Collection</collection><collection>Engineering Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Hrishav Bakul Barua</au><format>book</format><genre>document</genre><ristype>GEN</ristype><atitle>Data science and Machine learning in the Clouds: A Perspective for the Future</atitle><jtitle>arXiv.org</jtitle><date>2021-09-02</date><risdate>2021</risdate><eissn>2331-8422</eissn><abstract>As we are fast approaching the beginning of a paradigm shift in the field of science, Data driven science (the so called fourth science paradigm) is going to be the driving force in research and innovation. From medicine to biodiversity and astronomy to geology, all these terms are somehow going to be affected by this paradigm shift. The huge amount of data to be processed under this new paradigm will be a major concern in the future and one will strongly require cloud based services in all the aspects of these computations (from storage to compute and other services). Another aspect will be energy consumption and performance of prediction jobs and tasks within such a scientific paradigm which will change the way one sees computation. Data science has heavily impacted or rather triggered the emergence of Machine Learning, Signal/Image/Video processing related algorithms, Artificial intelligence, Robotics, health informatics, geoinformatics, and many more such areas of interest. Hence, we envisage an era where Data science can deliver its promises with the help of the existing cloud based platforms and services with the addition of new services. In this article, we discuss about data driven science and Machine learning and how they are going to be linked through cloud based services in the future. It also discusses the rise of paradigms like approximate computing, quantum computing and many more in recent times and their applicability in big data processing, data science, analytics, prediction and machine learning in the cloud environments.</abstract><cop>Ithaca</cop><pub>Cornell University Library, arXiv.org</pub><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | EISSN: 2331-8422 |
ispartof | arXiv.org, 2021-09 |
issn | 2331-8422 |
language | eng |
recordid | cdi_proquest_journals_2569853219 |
source | Free E- Journals |
subjects | Algorithms Artificial intelligence Astronomy Biodiversity Cloud computing Data processing Data science Energy consumption Image processing Machine learning Quantum computing Robotics Science Signal processing Video |
title | Data science and Machine learning in the Clouds: A Perspective for the Future |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-21T13%3A06%3A36IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=document&rft.atitle=Data%20science%20and%20Machine%20learning%20in%20the%20Clouds:%20A%20Perspective%20for%20the%20Future&rft.jtitle=arXiv.org&rft.au=Hrishav%20Bakul%20Barua&rft.date=2021-09-02&rft.eissn=2331-8422&rft_id=info:doi/&rft_dat=%3Cproquest%3E2569853219%3C/proquest%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2569853219&rft_id=info:pmid/&rfr_iscdi=true |