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
aziende
Abbiamo dati su 9 aziende che usano Amazon SageMaker Pipelines. La nostra lista di clienti Amazon SageMaker Pipelines è disponibile per il download ed è arricchita con specifiche vitali dell'azienda, incluse classificazione industriale, dimensioni organizzative, posizione geografica, round di finanziamenti e cifre di ricavi, tra gli altri.
Azienda | Paese | Settore | Dipendenti | Entrate |
---|---|---|---|---|
Grupo Nutresa | Colombia | Food And Beverage Manufacturing | 10K | $6.9M |
Siemens S.A. | Francia | Automation Machinery Manufacturing | 261K | $72B |
TMNL | Francia | Performing Arts | 5 | |
tCognition | Stati Uniti | It Services And It Consulting | 170 | $15M |
GlobalLogic UK&I | Regno Unito | It Services And It Consulting | 26K | $1.5B |
Verana Health | Stati Uniti | It Services And It Consulting | 230 | $22M |
Affine | Stati Uniti | Business Consulting And Services | 510 | $7M |
Siemens | Germania | Automation Machinery Manufacturing | 311K | $73B |
Vuoi scaricare l'intera lista?
Iscriviti e scarica l'elenco completo delle 9 aziende
Loading countries...
Loading other techonlogies...
Statistiche sull'Uso delle Tecnologie e Quota di Mercato
Puoi personalizzare questi dati secondo le tue necessità, filtrando per geografia, settore, dimensione dell'azienda, fatturato, uso della tecnologia, posizioni lavorative e altro ancora. Puoi scaricare i dati in formato Excel o CSV.
Puoi ricevere avvisi per questi dati. Puoi iniziare selezionando la tecnologia che ti interessa e poi riceverai avvisi nella tua casella di posta quando ci sono nuove aziende che utilizzano quella tecnologia.
Puoi esportare i suoi dati in un file Excel, che può essere importato nel tuo CRM. Puoi anche esportare i dati in un'API.
Amazon SageMaker Pipelines è utilizzata in 5 paesi
Ci sono 76 alternative a Amazon SageMaker Pipelines
21,6k
19,5k
6k
3,6k
3,3k
2,4k
2,3k
2k
1,8k
1,6k
1,3k
1,2k
1,1k
900
851
781
761
680
579
555
538
516
486
459
307
253
248
218
205
145
144
143
131
125
109
106
91
73
68
67
50
49
44
37
30
22
19
18
17
15
Domande frequenti
I nostri dati provengono da offerte di lavoro raccolte da milioni di aziende. Monitoriamo queste offerte sui siti web delle aziende, sui portali di lavoro e su altre piattaforme di reclutamento. Analizzare le offerte di lavoro offre un metodo affidabile per comprendere le tecnologie impiegate dalle aziende, inclusi i loro strumenti interni.
Aggiorniamo i nostri dati quotidianamente per garantire che tu abbia accesso alle informazioni più aggiornate disponibili. Questo processo di aggiornamento frequente garantisce che le nostre intuizioni e intelligenze riflettano gli ultimi sviluppi e tendenze all'interno dell'industria.
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.
Puoi accedere a un elenco aggiornato di aziende che utilizzano Amazon SageMaker Pipelines visitando TheirStack.com. La nostra piattaforma fornisce un database completo di aziende che utilizzano varie tecnologie e strumenti interni.
Fino ad ora, abbiamo dati su 9 aziende che utilizzano Amazon SageMaker Pipelines.
Amazon SageMaker Pipelines è utilizzato da una vasta gamma di organizzazioni in vari settori, inclusi "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". Per un elenco completo di tutti i settori che utilizzano Amazon SageMaker Pipelines, si prega di visitare TheirStack.com.
Alcune delle aziende che utilizzano Amazon SageMaker Pipelines includono Grupo Nutresa, Siemens S.A., TMNL, tCognition, GlobalLogic UK&I, Verana Health, Affine, Siemens e molte altre. Puoi trovare un elenco completo di 9 aziende che utilizzano Amazon SageMaker Pipelines su TheirStack.com.
Secondo i nostri dati, Amazon SageMaker Pipelines è più popolare in Stati Uniti (3 companies), Francia (2 companies), Colombia (1 companies), Germania (1 companies), Regno Unito (1 companies). Tuttavia, è utilizzato da aziende in tutto il mondo.
Puoi trovare aziende che utilizzano Amazon SageMaker Pipelines cercandolo su TheirStack.com. Tracciamo le offerte di lavoro di milioni di aziende e le utilizziamo per scoprire quali tecnologie e strumenti interni stanno utilizzando.