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Forecasting COVID-19 cases at the Amazon region: a comparison of classical and machine learning models
[article]
2020
bioRxiv
pre-print
Preserved Fulltext
learning techniques viable options. ...
MATERIAL AND METHODS - We implement the models to data provided by the health surveillance secretary of Amapá, a Brazilian state fully carved in the Amazon rainforest, which has been experiencing high ...
Machine learning. 2001;45(1):5-32. 27. Yeşilkanat CM. Spatio-temporal estimation of the daily cases of COVID-19 in worldwide using random forest machine learning algorithm. ...
doi:10.1101/2020.10.09.332908
fatcat:qt3ryqddzrc7vnypbbqfl5j6le
MLbench
2018
Proceedings of the VLDB Endowment
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We then conduct an empirical study using MLBench to understand example machine learning services from Amazon and Microsoft Azure, and showcase how MLBench enables a comparative study revealing the strength ...
and weakness of these existing machine learning services quantitatively and systematically. ...
Amazon Machine Learning. ...
doi:10.14778/3231751.3231770
fatcat:hzitipxuvvhbreizch6tqdh4fi
An Incorporation of Artificial Intelligence Capabilities in Cloud Computing
2016
International Journal Of Engineering And Computer Science
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In this paper, discuss about artificial intelligence capabilities in cloud computing, in the form of cloud machine learning platforms and artificial intelligence cloud services. ...
They provides cloud machine learning platform and artificial intelligence cloud services like computer vision, powerful speech recognition, powerful text analysis, fast dynamic translation, smart search ...
Amazon Machine Learning is highly scalable and can generate billions of predictions daily, and serve those predictions in real time and at high throughput with Amazon Machine Learning, there is no upfront ...
doi:10.18535/ijecs/v5i11.63
fatcat:o5wbltjolfefpedjzcpgn62wzy
MLBench: How Good Are Machine Learning Clouds for Binary Classification Tasks on Structured Data?
[article]
2017
arXiv
pre-print
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We then compare the performance of the top winning code available from Kaggle with that of running machine learning clouds from both Azure and Amazon on mlbench. ...
Machine learning clouds hold the promise of hiding all the sophistication of running large-scale machine learning: Instead of specifying how to run a machine learning task, users only specify what machine ...
Studio and Amazon Machine Learning. ...
arXiv:1707.09562v3
fatcat:lolzimetufetlpjlh635xl5fkm
Machine learning in the real world
2016
Proceedings of the VLDB Endowment
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This tutorial takes a hands-on approach to introducing the audience to machine learning. ...
The first part of the tutorial gives a broad overview and discusses some of the key concepts within machine learning. ...
Gourav Roy is a Software Engineer in the Machine Learning team at Amazon where he builds scalable machine learning platforms and applications. ...
doi:10.14778/3007263.3007318
fatcat:afaxvtczn5hhharfciqc4huu3e
Bringing Gaming; VR; and AR to Life with Deep Learning
2017
Proceedings of the 2017 ACM on Multimedia Conference - MM '17
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Lange is VP of AI and Machine Learning at Unity Technologies. ...
Prior to Amazon, Danny was Principal Development Manager at Microsoft where he was leading a product team focused on large-scale Machine Learning for Big Data. ...
doi:10.1145/3123266.3130873
dblp:conf/mm/Lange17
fatcat:jeiwusoajvdnjfvbt2p23g3lom
Building Machine Learning Based Senti-word Lexicon for Sentiment Analysis
2011
Journal of Advances in Information Technology
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We propose a Machine Learning Based Senti-word Lexicon (MLBSL) based on the Amazon data set which contains reviews from different domains. ...
In this paper we proposed a Machine Learning Based Senti-word Lexicon based on the Amazon data set which contains reviews from different domains. ...
Figure 1 . 1 Creating Machine Learning Based Senti-word Lexicon Using Amazon Data set
TABLE 1 : 1 THE RESULTS OF AMAZON AND MOVIES REVIEWS CLASSIFICATION USING MLBSL BASED ON 'NORMAL REVIEWS' AND 'STRING ...
doi:10.4304/jait.2.4.199-203
fatcat:q4pyd4ejgnajnjlikn3owcxxya
Sentiment Analysis of Product Reviews to Identify Deceptive Rating Information in Social Media: A SentiDeceptive Approach
2022
KSII Transactions on Internet and Information Systems
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learning classifiers. ...
learning algorithms by applying a standard crossvalidation approach (KFold and Shuffle Split). ...
The details about the machine learning algorithms and experiment are discussed below:
Machine Learning Algorithms To identify deceptive end-user rating information in the Amazon and Flipkart shopping ...
doi:10.3837/tiis.2022.03.005
fatcat:yqf7rdyxqvgx5gy5aytwrjst3a
Cloud-based Healthcare data management Framework
2020
KSII Transactions on Internet and Information Systems
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Finally, a cloud-based healthcare architecture using Amazon Cloud Services is constructed for reference. ...
The top three public cloud providers-Amazon, Google, and Microsoft offers advanced cloud services for the solution that the healthcare industry is looking for. ...
Amazon ElasticSearch
Bigquery,
Cloud ML,
Cloud Dataprep
Azure Data
Explorer,Azure
Databricks,Analysis
Services
Machine Learning
Amazon Sage Maker
Cloud Machine
Learning
Engine,AutoML, ...
doi:10.3837/tiis.2020.03.006
fatcat:yeput45l7favbmvt2hhwjfsn5y
Machine Learning for the Communication Optimization in Distributed Systems
2018
International Journal of Engineering & Technology
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Machine Learning tools had been retained from the cloud services provider – Amazon Web Services. ...
learning. ...
The machine learning tools are available at the Amazon Web Services (further -AWS), including the following options of supervised learning [5] : 1. binary classificationreference of a vector of values ...
doi:10.14419/ijet.v7i4.1.19491
fatcat:yrcqecermzgrtc7ecrvfgbacpa
Machine learning with cloud platforms
2021
Zenodo
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This paper presents a general overview of how machine learning solutions may be implemented using modern cloud platforms. ...
machine learning [8] . ...
AutoML Vision automates the training of custom machine learning models. Vision API offers powerful pretrained machine learning models through REST and RPC APIs. ...
doi:10.5281/zenodo.5555430
fatcat:jys6ar46szbrdkupfkhkuxvjim
Transferability in Machine Learning: from Phenomena to Black-Box Attacks using Adversarial Samples
[article]
2016
arXiv
pre-print
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We demonstrate our attacks on two commercial machine learning classification systems from Amazon (96.19% misclassification rate) and Google (88.94%) using only 800 queries of the victim model, thereby ...
Many machine learning models are vulnerable to adversarial examples: inputs that are specially crafted to cause a machine learning model to produce an incorrect output. ...
Amazon Web Services Oracle Amazon offers a machine learning service, Amazon Machine Learning, 4 as part of their Amazon Web Services platform. ...
arXiv:1605.07277v1
fatcat:mlnntpsmbnfe3gahi7a3u77rlu
Comparison of cloud computing providers for development of big data and internet of things application
2021
Indonesian Journal of Electrical Engineering and Computer Science
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learning. ...
analyzed several parameters such as technology specifications, model services, data center location, big data service, internet of things, microservices architecture, cloud computing management, and machine ...
Learning
Image Search, Machine
Translation, Machine
Learning Platform For
AI, Intelligent Speech
InteractionBeta
GCP
Amazon SageMaker,
Amazon Augmented AI,
Amazon CodeGuru
(Preview), Amazon ...
doi:10.11591/ijeecs.v22.i3.pp1723-1730
fatcat:jfsptxeti5bhffoi5ywor3vboa
Application of Quantum Machine Learning using the Quantum Kernel Algorithm on High Energy Physics Analysis at the LHC
[article]
2021
arXiv
pre-print
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Quantum machine learning could possibly become a valuable alternative to classical machine learning for applications in High Energy Physics by offering computational speed-ups. ...
study using up to 20 qubits and up to 50000 events, the QSVM-Kernel method performs as well as its classical counterparts in three different platforms from Google Tensorflow Quantum, IBM Quantum and Amazon ...
Due to the small ttH production rate at the LHC, its observation was highly challenging. The ATLAS and CMS analyses utilize machine learning techniques to improve the sensitivities to ttH production. ...
arXiv:2104.05059v1
fatcat:kfhucj2oe5hj7b7xvsgoylgzqy
Product Sentiment Analysis for Amazon Reviews
2021
Zenodo
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This Research Provides an Analysis of the Amazon Reviews Dataset and Studies Sentiment Classification with Different Machine Learning Approaches. ...
Then, we Trained Various Machine Learning Algorithms, I.E., Logistic Regression, Random Forest, Naïve Bayes, Bidirectional Long-Short Term Memory, and Bert. ...
On the other hand, machine learning techniques are divided into: supervised learning, and unsupervised learning. ...
doi:10.5281/zenodo.5100054
fatcat:5bxaueg4vffyvn6foo5ukugx5y
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