AI News, Introducing the AWS Machine Learning Competency for Consulting Partners

Introducing the AWS Machine Learning Competency for Consulting Partners

This AWS Competency program allows APN Consulting Partners to demonstrate a deep expertise in machine learning on AWS by providing solutions that enable machine learning and data science workflows for their customers.

These APN Consulting Partners help organizations solve their machine learning and data challenges through: The AWS Competency Program helps customers find the most qualified partners with deep expertise.

AWS Machine Learning Competency Partners undergo a strict validation of their capabilities to demonstrate technical proficiency and proven customer success with AWS machine learning tools.

C3 IoT Achieves Amazon Web Services’ Machine Learning Competency

Las Vegas, Nevada – November 29, 2017 – Today at AWS re:Invent 2017, the premier event for the global cloud computing community, C3 IoT announced it has achieved the Amazon Web Services (AWS) Machine Learning Competency, which was unveiled during the AWS Global Partner Summit.

The C3 Type System, found at the heart of all C3 IoT products, allows data scientists to easily and intuitively access a unified data image, rapidly develop Machine Learning features and train predictive models, and seamlessly deploy these models into production applications.

“C3 IoT leverages AWS to enable organizations to rapidly apply these innovative technologies to achieve productivity improvements, cost efficiencies, and higher levels of customer service.”

DataRobot Achieves AWS Machine Learning Competency Status

November 28, 2017 — DataRobot, a pioneer in automated machine learning (ML), announced today that it has achieved Amazon Web Services (AWS) ML Competency status. The designation recognizes DataRobot for providing business analysts, data scientists and machine learning practitioners with an automated, cutting-edge solution that enables predictive capabilities within customer applications.

“Achieving AWS ML Competency status recognizes our track record of excellence in automated machine learning, as well as our dedication to our users, many of whom rely on AWS to power their data-driven initiatives.” The DataRobot automated machine learning platform puts the power of ML into the hands of any business user.

By automating routine tasks, teams are able focus squarely on the problems they are trying to solve and spend less time worrying about how to optimize and deploy their models.” AWS is enabling scalable, flexible, and cost-effective solutions from startups to global enterprises.

Incorporating a library of hundreds of the most powerful open source machine learning algorithms, the DataRobot platform automates, trains and evaluates predictive models in parallel, delivering more accurate predictions at scale.

Introducing the AWS Machine Learning Competency

The areas of artificial intelligence (AI) and machine learning (ML) are being applied to every imaginable use case—protecting users from fraud, improving customer experience, helping people discover entertainment easier, and predicting when maintenance is needed in industrial equipment.

To help take this growing market forward, we are proud to introduce the AWS Machine Learning Competency for APN Technology Partners, showcasing industry-leading APN Partners that help organizations solve their data challenges, enable machine learning and data science workflows, or offer SaaS-based capabilities that enhance applications with machine intelligence.

We’ve set a high bar to become an AWS Machine Learning Competency Partner, as we want to help customers identify and connect with APN Partners that can support them in multiple areas, including data services, platform solutions, and SaaS/API solutions.

To become an AWS Machine Learning Competency Partner, enterprises undergo a strict validation of their capabilities to demonstrate technical proficiency and proven customer success.

The AWS Data Services Launch Partners are: The next generation of platforms will provide environments where data scientists can take their data, train predictive models, and make predictions on new data.

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