AWS Machine Learning Competency Partners
Drive innovation and unlock greater business value with AWS Specialization Partners that have deep technical knowledge and proven customer success
AWS Machine Learning Competency Partners have demonstrated expertise delivering machine learning (ML) solutions on the AWS Cloud. These partners offer a range of services and technologies to help you create intelligent solutions for your business, from enabling data science workflows to enhancing applications with machine intelligence.
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Data processing such as ingestion, consolidation, removal of duplicate records, imputation of missing values, scaling/normalization of values, elimination of correlated features, feature engineering, and others.
No and low-code platforms for machine learning, usually with a predominantly visual interface, that enable end-to-end model development.
High-code solutions, RESTful API, GraphQL, and algorithms that provide access to trained models and components used to train models.
AWS ML Competency Partners have demonstrated expertise in helping organizations solve the most challenging problems in AI, including data engineering, data science, machine and deep learning, and production deployment for inference at scale.
Development, deployment, and maintenance of ML applications that positively impact customer business outcomes and add value on top of AWS services, in particular AWS AI Services, to solve specific customer needs.
Connect with AWS Machine Learning Competency Partners
Drive innovation, meet business objectives, and get the most out of your AWS services by partnering with technically validated AWS Partners.
Additional Resources
Discover more AWS Machine Learning Competency Partner solutions and resources.
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General Resources
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Success Stories
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APN TV
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eBooks
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General Resources
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Maximizing Your Machine Learning Investment
Explore AWS Machine Learning Competency Partner eBooks, webinars, customer success stories, and more.
Machine Learning Foundations
Watch the on-demand webinars and discover how these technologies are essential for digital transformations.
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Success Stories
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Media & Entertainment
Cloudar Helps Ladrokes.live Transform The Sports Fan Experience With Cloud-Native Scalability
BelgiumLadbrokes.live, a provider of streaming sports entertainment content operating in Belgium, was grappling with critical challenges that hindered their ability to attract and retain users. Partnering with AWS Partner, Cloudar—also based in Belgium—the company transitioned to a cloud-native architecture powered by Amazon Web Services (AWS) technologies. This transformation enabled Ladbrokes.live to deliver a seamless, personalized user experience featuring avatars that can be customized to deliver information and statistics relevant to the viewers’ interests, in their language of choice. The solution also helped Ladbrokes.live optimize operational costs and set the stage for continuous innovation in a highly competitive industry.
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General Public Services
Wildlife-Centered AI: How AWS and Tehanu Use Generative AI to Give Wildlife a Voice in Global Conservation
RwandaThe Tehanu project in Rwanda’s Volcanoes National Park has demonstrated groundbreaking use of generative AI to infer and act on the interests of mountain gorillas. Leveraging technology solutions from Amazon Web Services (AWS), AWS Partner Anthropic, and with the support of AWS Partner Adastra, Tehanu created an automated pipeline to process behavioral data of gorillas, enabling the first-ever digital financial transactions by a non-human species. The AI solution synthesized vast academic and observational data, aligning conservation actions with species-specific preferences while supporting biodiversity efforts. This scalable, innovative approach sets a precedent for using AI to foster coexistence across species worldwide.
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APN TV
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eBooks
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AI Solutions for Financial Services
Appen’s artificial intelligence (AI) experts explain how to identify and implement successful machine learning and AI initiatives.
Machine Learning Within Reach
Learn how to connect with Amazon SageMaker to develop, test, and deploy machine models at scale and take advantage of cost-effective, pay-as-you-go pricing.
Weave AI Into Your Business
Learn how to prepare for, embed, and put AI into production quickly to solve complex business problems.
Mining Your Data Lake for Analytics Insights
Learn about using Delta Lake on Databricks and AWS to prepare and deliver data that drives valuable analytics insights.
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Blogs
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Jason O'Malley, Claudio Medeiros, Maggie Osude, 03/26/2025This blog is co-authored by Jakub Abramczyk, Data Scientist, Sebastian Boruch, ChurnIQ Product Manager, and Kirstin White, Growth Marketing Manager from Cleeng. In the competitive direct-to-consumer (D2C) streaming market, understanding subscriber behavior is essential for increasing engagement, optimizing content, and reducing customer churn. According to Forbes, acquiring new customers costs 5-7 times more than retaining [...]
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Marc Karp, Benjamin Crabtree, Banu Nagasundaram, Niris Okram, 03/26/2025Today, we are announcing an enhanced private hub feature with several new capabilities that give organizations greater control over their ML assets. These enhancements include the ability to fine-tune SageMaker JumpStart models directly within the private hub, support for adding and managing custom-trained models, deep linking capabilities for associated notebooks, and improved model version management.
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Isha Dua, Parth Patel, 03/26/2025Generative AI has emerged as a game changer, offering unprecedented opportunities for game designers to push boundaries and create immersive virtual worlds. At the forefront of this revolution is Stability AI’s cutting-edge text-to-image AI model, Stable Diffusion 3.5 Large (SD3.5 Large), which is transforming the way we approach game environment creation. In this post, we explore how you can use SD3.5 Large to address practical gaming needs such as early concept art and character design.
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Jeff Kratz, 03/26/2025Today, Amazon Web Services (AWS) launched the 2025 AWS Imagine Grant cycle in six countries. The AWS Imagine Grant is a public grant opportunity open to registered nonprofit organizations who are using cloud technology to accelerate their missions. Now in its eighth year, the AWS Imagine Grant is expanding to nonprofits beyond the US, UK, and Ireland, adding Canada, Australia, and New Zealand.
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Joshua Jin, Barry Ooi, Camilo Leon, Sudarshan Roy, 10/30/2024In Part 1 of this post, we covered how Retrieval Augmented Generation (RAG) can be used to enhance responses in generative AI applications by combining domain-specific information with a foundation model (FM). However, we stayed focused on the semantic search aspect of the solution, assuming that our vector store was already built and fully populated. In this post, we explore how to generate vector embeddings on Wikipedia data stored in a SQL Server database hosted on Amazon RDS. We also use Amazon Bedrock to invoke the appropriate FM APIs and an Amazon SageMaker Jupyter Notebook to help us orchestrate the overall process.
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