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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.
9
entreprises
Nous disposons de données sur 9 entreprises qui utilisent Amazon SageMaker Pipelines. Notre liste de clients Amazon SageMaker Pipelines est disponible en téléchargement et est enrichie de spécificités essentielles de l'entreprise, y compris la classification de l'industrie, la taille de l'organisation, la localisation géographique, les tours de financement et les chiffres d'affaires, entre autres.
Entreprise | Pays | Industrie | Employés | Chiffre d'affaires |
---|---|---|---|---|
Grupo Nutresa | Colombie | Food And Beverage Manufacturing | 10K | $6.9M |
Siemens S.A. | France | Automation Machinery Manufacturing | 261K | $72B |
TMNL | France | Performing Arts | 5 | |
tCognition | États-Unis | It Services And It Consulting | 170 | $15M |
GlobalLogic UK&I | Royaume-Uni | It Services And It Consulting | 26K | $1.5B |
![]() Verana Health | États-Unis | It Services And It Consulting | 230 | $22M |
Affine | États-Unis | Business Consulting And Services | 510 | $7M |
Siemens | Allemagne | Automation Machinery Manufacturing | 311K | $73B |
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Statistiques d'Utilisation Technologique et Part de Marché
Vous pouvez personnaliser ces données selon vos besoins en filtrant par géographie, secteur d'activité, taille de l'entreprise, revenus, utilisation de la technologie, postes de travail et plus encore. Vous pouvez télécharger les données au format Excel ou CSV.
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Questions fréquemment posées
Nos données proviennent d'offres d'emploi collectées auprès de millions d'entreprises. Nous surveillons ces offres sur les sites web des entreprises, les plateformes d'emploi et d'autres plateformes de recrutement. L'analyse des offres d'emploi constitue une méthode fiable pour comprendre les technologies utilisées par les entreprises, y compris l'utilisation de leurs outils internes.
Nous actualisons nos données quotidiennement pour vous garantir un accès à l'information la plus récente disponible. Ce processus de mise à jour fréquente assure que nos insights et notre intelligence reflètent les derniers développements et tendances au sein de l'industrie.
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.
Vous pouvez accéder à une liste actualisée des entreprises utilisant Amazon SageMaker Pipelines en visitant TheirStack.com. Notre plateforme fournit une base de données complète des entreprises utilisant diverses technologies et outils internes.
À ce jour, nous disposons de données sur 9 entreprises qui utilisent Amazon SageMaker Pipelines.
Amazon SageMaker Pipelines est utilisé par une large gamme d'organisations dans divers secteurs, y compris "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". Pour une liste complète de tous les secteurs utilisant Amazon SageMaker Pipelines, veuillez visiter TheirStack.com.
Certaines des entreprises qui utilisent Amazon SageMaker Pipelines incluent Grupo Nutresa, Siemens S.A., TMNL, tCognition, GlobalLogic UK&I, Verana Health, Affine, Siemens et bien d'autres encore. Vous pouvez trouver une liste complète des 9 entreprises qui utilisent Amazon SageMaker Pipelines sur TheirStack.com.
Selon nos données, Amazon SageMaker Pipelines est le plus populaire dans États-Unis (3 companies), France (2 companies), Colombie (1 companies), Allemagne (1 companies), Royaume-Uni (1 companies). Toutefois, il est utilisé par des entreprises du monde entier.
Vous pouvez trouver des entreprises utilisant Amazon SageMaker Pipelines en le recherchant sur TheirStack.com. Nous suivons les offres d'emploi de millions d'entreprises et les utilisons pour découvrir quelles technologies et outils internes elles emploient.
Amazon SageMaker Pipelines est utilisé dans 5 pays