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It is the first purpose-built, easy-to-use continuous integration and continuous delivery (CI/CD) service for machine learning (ML). With SageMaker Pipelines, you can create, automate, and manage end-to-end ML workflows at scale.
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Unternehmen
Wir haben Daten zu 9 Unternehmen, die Amazon SageMaker Pipelines verwenden. Unsere Amazon SageMaker Pipelines Kundenliste steht zum Download bereit und ist mit wichtigen Unternehmensspezifika angereichert, darunter Branchenklassifikation, Organisationsgröße, geografische Lage, Finanzierungsrunden und Umsatzzahlen, unter anderem.
Unternehmen | Land | Branche | Mitarbeiter | Umsatz |
---|---|---|---|---|
Grupo Nutresa | Kolumbien | Food And Beverage Manufacturing | 10K | $6.9M |
Siemens S.A. | Frankreich | Automation Machinery Manufacturing | 261K | $72B |
TMNL | Frankreich | Performing Arts | 5 | |
tCognition | Vereinigte Staaten | It Services And It Consulting | 170 | $15M |
GlobalLogic UK&I | Vereinigtes Königreich | It Services And It Consulting | 26K | $1.5B |
Verana Health | Vereinigte Staaten | It Services And It Consulting | 230 | $22M |
Affine | Vereinigte Staaten | Business Consulting And Services | 510 | $7M |
Siemens | Deutschland | Automation Machinery Manufacturing | 311K | $73B |
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Nutzungsstatistiken für Technologie und Marktanteil
Sie können diese Daten an Ihre Bedürfnisse anpassen, indem Sie nach Geografie, Branche, Unternehmensgröße, Umsatz, Technologienutzung, Jobpositionen und mehr filtern. Sie können die Daten im Excel- oder CSV-Format herunterladen.
Sie können Alarme für diese Daten erhalten. Sie können beginnen, indem Sie die Technologie auswählen, die Sie interessiert, und dann erhalten Sie Alarme in Ihrem Posteingang, wenn es neue Unternehmen gibt, die diese Technologie verwenden.
Sie können seine Daten in eine Excel-Datei exportieren, die in Ihr CRM importiert werden kann. Sie können die Daten auch an eine API exportieren.
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Amazon SageMaker Pipelines wird in 5 Ländern verwendet
Häufig gestellte Fragen
Unsere Daten stammen aus Stellenanzeigen, die von Millionen von Unternehmen gesammelt wurden. Wir überwachen diese Anzeigen auf Firmenwebseiten, Jobbörsen und anderen Rekrutierungsplattformen. Die Analyse von Stellenanzeigen bietet eine zuverlässige Methode, um die von Unternehmen verwendeten Technologien zu verstehen, einschließlich der Nutzung interner Tools.
Wir aktualisieren unsere Daten täglich, um sicherzustellen, dass Sie auf die aktuellsten verfügbaren Informationen zugreifen. Dieser häufige Aktualisierungsprozess garantiert, dass unsere Einsichten und Erkenntnisse die neuesten Entwicklungen und Trends der Branche widerspiegeln.
Amazon SageMaker Pipelines is a sophisticated technology within the realm of Machine Learning Tools, designed to streamline the process of building, managing, and deploying machine learning workflows. It enables data scientists and developers to create end-to-end ML pipelines that are efficient, scalable, and easy to reproduce. By providing a visual interface for building workflows, Amazon SageMaker Pipelines simplifies the complexity of managing ML tasks, allowing users to focus more on the development and optimization of models.
Amazon SageMaker Pipelines falls under the category of Machine Learning Tools, specifically focusing on pipeline orchestration and automation. This technology helps in structuring ML workflows by defining each step from data preparation to model deployment, ensuring a cohesive and efficient process. It allows for versioning of each step, facilitating reproducibility and collaboration among team members working on ML projects. With features like automated retraining and model monitoring, Amazon SageMaker Pipelines enhances the efficiency of machine learning development cycles.
Founded by Amazon Web Services, Amazon SageMaker Pipelines originated from the growing need to simplify and streamline the machine learning workflow process for data scientists and developers. Launched as part of the Amazon SageMaker ecosystem, the technology aimed to address the challenges faced in managing complex ML pipelines and enable faster experimentation and deployment of models. Since its inception, Amazon SageMaker Pipelines has gained significant traction in the market, establishing itself as a prominent player in the Machine Learning Tools category.
In terms of current market share, Amazon SageMaker Pipelines holds a strong position within the Machine Learning Tools category. With the increasing adoption of machine learning technologies across various industries, the demand for robust pipeline orchestration tools like Amazon SageMaker Pipelines is expected to grow further. Industry forecasts suggest a positive outlook for the technology, indicating a potential increase in market share as organizations continue to invest in optimizing their machine learning workflows.
Amazon SageMaker Pipelines is a powerful tool that allows companies to streamline and automate their machine learning workflows efficiently. By leveraging this technology, businesses can achieve greater operational efficiency, scalability, and collaboration among their teams. Below are some key benefits of using Amazon SageMaker Pipelines:
Amazon SageMaker Pipelines simplifies the process of orchestrating complex workflows by providing a visually intuitive interface. Unlike traditional methods that require manual intervention and coding, SageMaker Pipelines automates the workflow, reducing errors and increasing productivity.
With SageMaker Pipelines, companies can easily track and manage different versions of their machine learning models and datasets. This level of version control ensures reproducibility and enables teams to collaborate seamlessly, unlike other technologies that may lack robust versioning capabilities.
Amazon SageMaker Pipelines enables rapid experimentation and deployment of machine learning models by automating the end-to-end workflow. This acceleration in the development cycle gives companies a competitive edge compared to relying on traditional methods that are time-consuming and manual.
By using Amazon SageMaker Pipelines, companies can monitor the performance of their machine learning models in real-time and optimize them with ease. This streamlined process of monitoring and optimizing models sets SageMaker Pipelines apart from other technologies that may lack integrated monitoring capabilities.
In summary, Amazon SageMaker Pipelines offers a comprehensive solution for companies looking to enhance their machine learning workflows, providing a robust platform for automation, collaboration, and efficiency.
Introduction:
Amazon SageMaker Pipelines is a powerful tool used by various companies to streamline and automate machine learning workflows. Several prominent companies have successfully leveraged Amazon SageMaker Pipelines to enhance their machine learning capabilities and drive innovation in their respective industries. Below are some insightful case studies showcasing how companies have benefited from utilizing Amazon SageMaker Pipelines in their operations.
Case Studies:
1. Zalando: Zalando, a leading fashion e-commerce platform, utilizes Amazon SageMaker Pipelines to automate their machine learning workflows for improving personalized recommendations. By implementing SageMaker Pipelines, Zalando has significantly reduced the time taken to develop and deploy machine learning models, enabling them to deliver more accurate and relevant product recommendations to their customers. Zalando began using Amazon SageMaker Pipelines in early 2020 and has since experienced enhanced operational efficiency and increased customer engagement.
2. Intuit: Intuit, a renowned financial software company, has integrated Amazon SageMaker Pipelines into their machine learning infrastructure to streamline the development and deployment of predictive analytics models. Intuit leverages SageMaker Pipelines to automate data processing, model training, and deployment processes, allowing them to deliver data-driven insights to their users more rapidly. Since adopting Amazon SageMaker Pipelines in late 2019, Intuit has seen a marked improvement in the speed and accuracy of their machine learning initiatives.
3. Cerner Corporation: Cerner Corporation, a prominent healthcare technology company, has embraced Amazon SageMaker Pipelines to enhance their healthcare analytics capabilities. By leveraging SageMaker Pipelines, Cerner Corporation has automated the end-to-end machine learning workflow for analyzing patient data and predicting healthcare outcomes. The implementation of Amazon SageMaker Pipelines has enabled Cerner Corporation to accelerate the development of advanced healthcare solutions while ensuring data security and compliance. They started using Amazon SageMaker Pipelines in 2021 and have since witnessed significant improvements in their data-driven decision-making processes.
These case studies highlight the diverse applications of Amazon SageMaker Pipelines across different industries and underscore the significant impact it can have on driving innovation and efficiency in machine learning projects.
Sie können eine aktuelle Liste von Unternehmen, die Amazon SageMaker Pipelines verwenden, auf TheirStack.com einsehen. Unsere Plattform bietet eine umfassende Datenbank von Unternehmen, die verschiedene Technologien und interne Tools nutzen.
Bis jetzt haben wir Daten von 9 Unternehmen, die Amazon SageMaker Pipelines verwenden.
Amazon SageMaker Pipelines wird von einer Vielzahl von Organisationen in verschiedenen Branchen, einschließlich "Food And Beverage Manufacturing", "Automation Machinery Manufacturing", "Performing Arts", "It Services And It Consulting", "It Services And It Consulting", "It Services And It Consulting", "Business Consulting And Services", "Automation Machinery Manufacturing", verwendet. Für eine umfassende Liste aller Branchen, die Amazon SageMaker Pipelines nutzen, besuchen Sie bitte TheirStack.com.
Einige der Unternehmen, die Amazon SageMaker Pipelines verwenden, umfassen Grupo Nutresa, Siemens S.A., TMNL, tCognition, GlobalLogic UK&I, Verana Health, Affine, Siemens und viele mehr. Sie können eine vollständige Liste von 9 Unternehmen, die Amazon SageMaker Pipelines nutzen, auf TheirStack.com finden.
Basierend auf unseren Daten ist Amazon SageMaker Pipelines am beliebtesten in Vereinigte Staaten (3 companies), Frankreich (2 companies), Kolumbien (1 companies), Deutschland (1 companies), Vereinigtes Königreich (1 companies). Es wird jedoch von Unternehmen auf der ganzen Welt verwendet.
Sie können Unternehmen, die Amazon SageMaker Pipelines verwenden, finden, indem Sie auf TheirStack.com danach suchen. Wir verfolgen Stellenanzeigen von Millionen von Unternehmen und nutzen sie, um herauszufinden, welche Technologien und internen Tools sie verwenden.