Filters








47 Hits in 2.8 sec

Elastic Machine Learning Algorithms in Amazon SageMaker

Edo Liberty, Zohar Karnin, Bing Xiang, Laurence Rouesnel, Baris Coskun, Ramesh Nallapati, Julio Delgado, Amir Sadoughi, Yury Astashonok, Piali Das, Can Balioglu, Saswata Chakravarty (+12 others)
2020 Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data  
SageMaker is an ML platform provided as part of Amazon Web Services (AWS), and supports incremental training, resumable and elastic learning as well as automatic hyperparameter optimization.  ...  There is a large body of research on scalable machine learning (ML).  ...  In this paper, we present the computational model (Section 2) and algorithms (Section 3) of Amazon SageMaker, a system for scalable, elastic model training on large streams of data, available as part of  ... 
doi:10.1145/3318464.3386126 dblp:conf/sigmod/LibertyKXRCNDSA20 fatcat:q2qg45qsyvfzvmthkrtzmsfowa

Amazon SageMaker Autopilot: a white box AutoML solution at scale [article]

Piali Das, Valerio Perrone, Nikita Ivkin, Tanya Bansal, Zohar Karnin, Huibin Shen, Iaroslav Shcherbatyi, Yotam Elor, Wilton Wu, Aida Zolic, Thibaut Lienart, Alex Tang (+13 others)
2020 arXiv   pre-print
In this paper, we present Amazon SageMaker Autopilot: a fully managed system providing an automated ML solution that can be modified when needed.  ...  AutoML systems provide a black-box solution to machine learning problems by selecting the right way of processing features, choosing an algorithm and tuning the hyperparameters of the entire pipeline.  ...  In addition, machine learning algorithms usually have a long list of training pa- * Work done while at Amazon Web Services. 1 Amazon Web Services.  ... 
arXiv:2012.08483v2 fatcat:3bm4zaafmjb2lbsod7ztj6aqxq

Privacy-Preserving XGBoost Inference [article]

Xianrui Meng, Joan Feigenbaum
2020 arXiv   pre-print
In this paper, we propose a privacy-preserving XGBoost prediction algorithm, which we have implemented and evaluated empirically on AWS SageMaker.  ...  Although machine learning (ML) is widely used for predictive tasks, there are important scenarios in which ML cannot be used or at least cannot achieve its full potential.  ...  The ML module is run on the Amazon SageMaker platform, a fully managed machine learning service.  ... 
arXiv:2011.04789v4 fatcat:jvusu7gsojc2biejrj42gd6pga

AWS Corporate AI Use Cases

Brian Kan, Douglas Klein
2022 Zenodo  
KEYWORDS: AWS, Amazon Web Services AI, AWS Machine Learning, AWS Business Use Cases  ...  ABSTRACT: Amazon, with $469 Billion in sales in 2021, has established itself as a world-class user of AI, utilizing Machine Learning (ML) in its search engine to deliver desired results quickly - so millions  ...  The NGS platform deploys the machine learning tool Amazon SageMaker, which enables the NFL to rapidly create machine learning models capable of interpreting the flow of action (Hardesty 2021) .  ... 
doi:10.5281/zenodo.6945948 fatcat:6nfpnyeb3bcfdf3j23bk4c7cny

The ISTI Rapid Response on Exploring Cloud Computing 2018 [article]

Carleton Coffrin, James Arnold, Stephan Eidenbenz, Derek Aberle, John Ambrosiano, Zachary Baker, Sara Brambilla, Michael Brown, K. Nolan Carter, Pinghan Chu, Patrick Conry, Keeley Costigan, Ariane Eberhardt (+31 others)
2019 arXiv   pre-print
These demonstrations ranged from deploying proprietary software in a cloud environment to leveraging established cloud-based analytics workflows for processing scientific datasets.  ...  Science & Technology Institute's "Exploring Cloud Computing 2018" would like to thank Terence Joyce and Brady Jones from the Associate Directorate for Business Innovation (ADBI) for their technical support in  ...  Machine Learning SageMaker: SageMaker is a managed service that streamlines the process of building machine learning workflows.  ... 
arXiv:1901.01331v1 fatcat:cdkmje2agzfsdpyulbp4cxz22q

Enabling an Enterprise Data Management Ecosystem using Change Data Capture with Amazon Neptune

Bradley R. Bebee, Rahul Chander, Ankit Gupta, Ankesh Khandelwal, Sainath Mallidi, Michael Schmidt, Ronak Sharda, Bryan B. Thompson, Prashant Upadhyay
2019 International Semantic Web Conference  
In this demonstration, we will present Amazon Neptune's approach to synchronize graph data to external systems using Neptune's Change Data Capture (CDC) mechanism.  ...  While the data graph as such can be queried as an integrated data corpus using existing graph query languages (in Amazon Neptune, we support both SPARQL as a query language over RDF as well as Gremlin  ...  analytics services like Amazon Elastic MapReduce (EMR), and services such as Amazon SageMaker supporting machine learning workflows and algorithms on top of the data.  ... 
dblp:conf/semweb/BebeeCGKM0STU19 fatcat:2ck5jtwzizbdxfo22ue54xo2xe

An Automated Data Engineering Pipeline for Anomaly Detection of IoT Sensor Data [article]

Xinze Li, Baixi Zou
2021 arXiv   pre-print
The process involves the use of IoT sensors, Raspberry Pis, Amazon Web Services (AWS) and multiple machine learning techniques with the intent to identify anomalous cases for the smart home security system  ...  With data analytics and the use of machine learning/deep learning, it is made possible to learn the underlying patterns and make decisions based on what was learned from massive data generated from IoT  ...  With data analytics and the use of machine learning/deep learning, it has the ability to learn the underlying patterns and make decisions based on what was learned.  ... 
arXiv:2109.13828v1 fatcat:ste4fwe35jasxcxln4dlxqze5i

Serverless Model Serving for Data Science [article]

Yuncheng Wu, Tien Tuan Anh Dinh, Guoyu Hu, Meihui Zhang, Yeow Meng Chee, Beng Chin Ooi
2021 arXiv   pre-print
Machine learning (ML) is an important part of modern data science applications.  ...  Other findings include a large gap in cold start time between AWS and GCP serverless functions, and serverless' low sensitivity to changes in workloads or models.  ...  Machine Learning Serving Machine learning has shown great success in a wide range of data science applications [18, 21, 38] .  ... 
arXiv:2103.02958v1 fatcat:mdfnswimkfce3dxan6zjrliyfm

Data Analytics Architectures for E-Commerce Platforms in Cloud

John Yeung
2021 International Journal for Applied Information Management  
It also shows how to articulate data analytics frameworks for ecommerce platforms in the cloud and how to integrate machine learning models into data analytics processes, to create more sophisticated analyzes  ...  This cloud platform enables them to provide elasticity and efficient computing and storage resources. They also provide many ready-to-use tools for building data analytics in various stages.  ...  In our example, we are using Amazon SageMaker as the platform to build, train and deploy ML models on Cloud.  ... 
doi:10.47738/ijaim.v1i1.3 fatcat:kzjlh5eborfclg665s6kg4gkzi

Architecting in the Cloud - How Public Cloud Environments are Helping Software Architects

Smit Bharatkumar Mehta
2019 International Journal for Research in Applied Science and Engineering Technology  
Additionally we have done primary research to compare 3 noteworthy public cloud service providers like Amazon Web Services, Microsoft Azure, Google Cloud Platform.  ...  These services focus on a minor part of the applications which provide scalability and agility to the applications Keywords: AWS (Amazon Web Service), Microsoft Azure, GCP (Google Cloud Platform), Cloud  ...  It also offers machine learning service called Sagemaker and Lex using which you can build voice and text chat Bots, and as for the IOT devices it offers green gasps IOT messaging app and as for Microsoft  ... 
doi:10.22214/ijraset.2019.3031 fatcat:nowgp7zaqjgr5dlkbi4aaag4nm

Comparison of cloud computing providers for development of big data and internet of things application

Muhammad Fajrul Falah, Yohanes Yohanie Fridelin Panduman, Sritrusta Sukaridhoto, Arther Wilem Cornelius Tirie, M. Cahyo Kriswantoro, Bayu Dwiyan Satria, Saifudin Usman
2021 Indonesian Journal of Electrical Engineering and Computer Science  
learning.  ...  However, the increase in cloud computing service providers causes difficulties in determining the chosen service provider.  ...  ACKNOWLEDGEMENT This research was funded from "Applied Leading Research in Higher Education (in Indonesian Penelitian Terapan Unggulan Perguruan Tinggi)" by KEMENRISTEKDIKTI in 2020 with the funding scheme  ... 
doi:10.11591/ijeecs.v22.i3.pp1723-1730 fatcat:jfsptxeti5bhffoi5ywor3vboa

A Privacy-Preserving Distributed Architecture for Deep-Learning-as-a-Service [article]

Simone Disabato, Alessandro Falcetta, Alessio Mongelluzzo, Manuel Roveri
2020 arXiv   pre-print
Deep-learning-as-a-service is a novel and promising computing paradigm aiming at providing machine/deep learning solutions and mechanisms through Cloud-based computing infrastructures.  ...  This paper introduces a novel distributed architecture for deep-learning-as-a-service that is able to preserve the user sensitive data while providing Cloud-based machine and deep learning services.  ...  For this purpose, we relied on a set of Amazon Web Services (AWS) tools comprising Sagemaker, Elastic Container Registry (ECR), AWS Lambda, API Gateway, and S3.  ... 
arXiv:2003.13541v1 fatcat:7odeymgjpjanhgktj342smev2a

Artificial Intelligence Methods for Rapid Vascular Access Aneurysm Classification in Remote or In-Person Settings

Warren Krackov, Murat Sor, Rishi Razdan, Hanjie Zheng, Peter Kotanko
2021 Blood Purification  
We examined the beneficial role AI can play in noninvasively grading vascular access aneurysms to reduce high-morbidity events, such as rupture, in ESRD patients on hemodialysis.  ...  We achieved a >90% classification accuracy in the validation images.  ...  Conflict of Interest Statement P.K. and W.K. hold stocks in Fresenius Medical Care. The other authors declare no competing interest.  ... 
doi:10.1159/000515642 pmid:33857941 fatcat:h5vgaac56bahpmqg4b3p5orrp4

Practices and Infrastructures for Machine Learning Systems: An Interview Study in Finnish Organizations

Dennis Muiruri, Lucy Ellen Lwakatare, Jukka K. Nurminen, Tommi Mikkonen
2022 Computer  
Model training ML algorithm selection and transfer learning.  ...  Amazon S3: Amazon Simple Storage Service; GC: Google Cloud.  ...  Over the Rainbow: 21st Century Security & Privacy Podcast Tune in with security leaders of academia, industry, and government. www.computer.org/over-the-rainbow-podcast Subscribe Today Bob Blakley Bob  ... 
doi:10.1109/mc.2022.3161161 fatcat:ib4xtmw3njb4lmvktihfylzbn4

MLbench

Yu Liu, Hantian Zhang, Luyuan Zeng, Wentao Wu, Ce Zhang
2018 Proceedings of the VLDB Endowment  
In this paper, we try to facilitate the process of asking the following type of questions: How much will the users lose if we remove the support of functionality x from a machine learning service?  ...  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  ...  Very recently, Amazon launched a new machine learning service called SageMaker [11]. We have further evaluated these models  ... 
doi:10.14778/3231751.3231770 fatcat:hzitipxuvvhbreizch6tqdh4fi
« Previous Showing results 1 — 15 out of 47 results