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Azure Machine Learning is a fully-managed cloud service that enables data scientists and developers to efficiently embed predictive analytics into their applications, helping organizations use massive data sets and bring all the benefits of the cloud to machine learning.
2,903
Unternehmen
Wir haben Daten zu 2,903 Unternehmen, die Azure Machine Learning verwenden. Unsere Azure Machine Learning 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 |
---|---|---|---|---|
Microsoft | Vereinigte Staaten | Software Development | 233K | $198B |
EY | Vereinigtes Königreich | Professional Services | 357K | $45B |
Avanade | Vereinigte Staaten | It Services And It Consulting | 19K | $2B |
Freeport McMoRan | Vereinigte Staaten | Mining | 10K | $15B |
Navy Federal Credit Union | Vereinigte Staaten | Financial Services | 22K | $6.9B |
Accenture | Irland | Business Consulting And Services | 738K | $63B |
IBM | Vereinigte Staaten | It Services And It Consulting | 309K | $61B |
PTV Planung Transport Verkehr | Deutschland | Broadcast Media Production And Distribution | 51 | |
KPMG | Kanada | Accounting | 265K | $75M |
PTV Group | Deutschland | Software Development | 912 | |
Applied Information Sciences | Vereinigte Staaten | It Services And It Consulting | 760 | $77M |
![]() Enable | Vereinigtes Königreich | Civic And Social Organizations | 1K | $18M |
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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.
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Azure Machine Learning wird in 57 Ländern verwendet
Es gibt 18 Alternativen zu Azure Machine Learning
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.
Azure Machine Learning is a powerful cloud-based service provided by Microsoft as part of the Azure cloud platform. It is designed to enable data scientists and developers to build, train, deploy, and manage machine learning models more easily and efficiently. With Azure Machine Learning, users can leverage a range of tools and frameworks to accelerate the development of AI solutions, from data preparation and model training to deployment and monitoring.
Machine Learning as a Service (MLaaS) is the category under which Azure Machine Learning falls. MLaaS platforms like Azure Machine Learning provide a set of tools and infrastructure for organizations to develop machine learning models without the need to build and maintain the underlying infrastructure. This category allows businesses to harness the power of machine learning algorithms and AI technologies to derive insights, improve decision-making processes, and enhance their products and services.
Azure Machine Learning was founded by Microsoft in 2014 with the aim of democratizing AI and making machine learning more accessible to a broader audience. Microsoft's motivation behind launching Azure Machine Learning was to empower organizations of all sizes to leverage the potential of AI and machine learning to drive innovation and accelerate digital transformation. Since its inception, Azure Machine Learning has gained significant traction in the market and established itself as a leading MLaaS platform.
Currently, Azure Machine Learning holds a substantial market share within the MLaaS category, thanks to Microsoft's strong presence in the cloud computing industry and its continuous investment in AI technologies. With the growing demand for AI-driven solutions across various industries, the market share of Azure Machine Learning is expected to continue expanding in the future. As organizations increasingly prioritize AI capabilities to gain a competitive edge and improve operational efficiency, Azure Machine Learning is poised to experience further growth and adoption in the market.
Azure Machine Learning is a powerful tool that companies utilize to harness the potential of machine learning for their business growth. With the advancements in Machine Learning as a Service (MLaaS) technology, Azure Machine Learning provides a robust platform for organizations to develop, deploy, and manage machine learning models efficiently.
Increased Productivity:
Azure Machine Learning streamlines the entire machine learning workflow, from data preparation to model deployment, enabling teams to focus on innovation rather than infrastructure management. Unlike traditional methods, Azure ML simplifies the process by offering a user-friendly interface and automated machine learning capabilities, reducing the time and effort required to deliver impactful solutions.
Scalability and Flexibility:
One of the key advantages of Azure Machine Learning is its scalability and flexibility. Companies can seamlessly scale resources up or down based on demand, ensuring optimal performance and cost-efficiency. This dynamic scalability sets Azure ML apart from on-premises solutions, allowing organizations to adapt to changing business requirements without significant investments in hardware.
Integrated Ecosystem:
Azure Machine Learning integrates seamlessly with other Microsoft Azure services, creating a comprehensive ecosystem that facilitates end-to-end machine learning solutions. This tight integration enables data scientists and developers to leverage diverse tools and services within the Azure platform, enhancing collaboration and productivity across teams. The cohesive ecosystem of Azure ML simplifies the development and deployment of machine learning models, providing a unified environment for experimentation and innovation.
In conclusion, Azure Machine Learning offers a comprehensive and user-friendly platform that empowers companies to accelerate their machine learning initiatives, drive innovation, and gain a competitive edge in today's rapidly evolving digital landscape.
Azure Machine Learning is a powerful tool used by various companies to harness the capabilities of Machine Learning as a Service. Here are some real-world case studies showcasing how companies leverage Azure Machine Learning for their business needs:
1. Adobe
Adobe, a renowned software company, utilizes Azure Machine Learning to enhance its marketing strategies. By leveraging Azure Machine Learning, Adobe can analyze vast amounts of customer data to generate insights for targeted marketing campaigns. Adobe started incorporating Azure Machine Learning into its operations in 2017, revolutionizing its approach to customer engagement.
2. Shell
Shell, a global energy company, harnesses Azure Machine Learning to optimize its drilling operations. By implementing Azure Machine Learning algorithms, Shell can predict equipment failures, analyze seismic data efficiently, and streamline its drilling processes. Shell adopted Azure Machine Learning in 2016, significantly boosting its operational efficiency and cost-effectiveness.
3. HP
HP, a leading technology company, employs Azure Machine Learning to improve its customer support services. By utilizing Azure Machine Learning models, HP can predict customer issues before they occur, provide proactive support, and enhance overall customer satisfaction. HP integrated Azure Machine Learning into its support operations in 2018, leading to a marked improvement in customer experience.
These case studies demonstrate the diverse applications of Azure Machine Learning across industries, showcasing how companies leverage this technology to drive innovation, improve operations, and deliver superior services to their customers.
Sie können eine aktuelle Liste von Unternehmen, die Azure Machine Learning 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 2,903 Unternehmen, die Azure Machine Learning verwenden.
Azure Machine Learning wird von einer Vielzahl von Organisationen in verschiedenen Branchen, einschließlich "Software Development", "Professional Services", "It Services And It Consulting", "Mining", "Financial Services", "Business Consulting And Services", "It Services And It Consulting", "Broadcast Media Production And Distribution", "Accounting", "Software Development", verwendet. Für eine umfassende Liste aller Branchen, die Azure Machine Learning nutzen, besuchen Sie bitte TheirStack.com.
Einige der Unternehmen, die Azure Machine Learning verwenden, umfassen Microsoft, EY, Avanade, Freeport McMoRan, Navy Federal Credit Union, Accenture, IBM, PTV Planung Transport Verkehr, KPMG, PTV Group und viele mehr. Sie können eine vollständige Liste von 2,903 Unternehmen, die Azure Machine Learning nutzen, auf TheirStack.com finden.
Basierend auf unseren Daten ist Azure Machine Learning am beliebtesten in Vereinigte Staaten (972 companies), Vereinigtes Königreich (257 companies), Deutschland (134 companies), Kanada (106 companies), Indien (91 companies), Frankreich (88 companies), Spanien (63 companies), Niederlande (58 companies), Brasilien (42 companies), Australien (39 companies). Es wird jedoch von Unternehmen auf der ganzen Welt verwendet.
Sie können Unternehmen, die Azure Machine Learning 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.