At DataRobot, we’re dedicated to serving to our prospects maximize the worth they achieve from our AI Platform. At the moment, we’re excited to share that DataRobot has joined the Amazon SageMaker Prepared Program. This designation helps prospects uncover associate software program options which might be validated by Amazon Net Companies (AWS) Accomplice Options Architects to combine with Amazon SageMaker. Our associate ecosystem is a key driver in guaranteeing buyer success, and partnering with AWS gives prospects with deep integrations that amplify the productiveness of knowledge science groups.
DataRobot and SageMaker create a strong duo to speed up AI adoption
With DataRobot AI Manufacturing, customers can construct their very own SageMaker containers to coach AI fashions and host them as a SageMaker endpoint, leveraging DataRobot MLOps libraries to mechanically accumulate and monitor inference metrics. Monitoring jobs may be scheduled natively from DataRobot with out the effort of guide pipelines, liberating up knowledge science sources whereas providing customers full observability throughout a lot of SageMaker fashions. Along with conventional MLOps actions, DataRobot AI Manufacturing provides out-of-the-box governance greatest practices reminiscent of automated mannequin compliance documentation and mannequin versioning so all DataRobot and SageMaker fashions may be ruled centrally.
Collectively, DataRobot and AWS present a seamless integration that matches the environment and permits higher, quicker data-driven selections with confidence. As DataRobot and AWS now turn into much more aligned, the potential to additional leverage the strengths of each platforms with simplified workflows, enhanced scalability and accelerated time-to-market is tremendously thrilling.
We’re thrilled to be a acknowledged Amazon SageMaker Prepared Accomplice, and sit up for serving to corporations obtain their expertise targets by leveraging AWS. To be taught extra about DataRobot’s integration with Amazon SageMaker, obtain the whitepaper right here.
In regards to the SageMaker Prepared Program
Becoming a member of the Amazon SageMaker Prepared Program differentiates DatRobot as an AWS Accomplice Community (APN) member with a product that works with Amazon SageMaker and is usually out there for and totally helps AWS prospects. The Amazon SageMaker Prepared program helps prospects shortly and simply discover AWS Software program Path associate merchandise to assist speed up their machine studying adoption by offering out-of-the-box abstractions for commonest challenges in machine studying (ML) that construct on prime of the foundational capabilities Amazon SageMaker gives.
Amazon SageMaker provides a sturdy set of capabilities and AWS Companions add worth to additional broaden the capabilities by integrating with their options. By offering prospects a catalog of Software program Path associate options that raise the complexities of machine studying, the Amazon SageMaker Prepared Program will broaden the person base and enhance buyer adoption. Amazon SageMaker Prepared Program members additionally supply AWS prospects Amazon SageMaker-supported merchandise that provide Amazon SageMaker each in Software program Path Accomplice options they already know, or supply merchandise that simplify every step of the ML mannequin constructing. These functions are validated by AWS Accomplice Options Architects to make sure prospects have a constant expertise utilizing the software program.
To assist the seamless integration and deployment of those options, AWS established the AWS Service Prepared Program to assist prospects determine options that assist AWS providers and spend much less time evaluating new instruments, and extra time scaling their use of options that work on AWS. Prospects can evaluate the Amazon SageMaker Prepared Accomplice product catalog to verify their most well-liked vendor options are already built-in with Amazon SageMaker. Prospects also can uncover, browse by class or ML mannequin deployment challenges, and choose associate software program options for his or her particular ML improvement wants.
In regards to the creator
Ksenia Chumachenko is a Vice President of Alliances and Enterprise Improvement at DataRobot. She leads Cloud and Know-how Alliances world group, serving to purchasers get worth from AI via a wider Cloud and Information ecosystem.
Ksenia has greater than 20 years of expertise delivering technological options and creating associate ecosystems throughout product startups, ISVs, and system integrators. She has ardour for taking partnerships to the subsequent stage through collaboration, creativity, data-driven strategy, and group nurturing with profitable expertise in establishing associate channel and constructing groups in pre- and post-IPO knowledge startups.
Ksenia holds an MBA in International Enterprise and Entrepreneurship from NYU Stern College of Enterprise, and B.S. in Pc Science and Arithmetic from NYU Courant. In her free time she spends time within the San Francisco Bay Space along with her household; they take pleasure in mountaineering, cooking and going to cultural occasions collectively.
Chen is Director of Accomplice Information Science at DataRobot, the place he drives product integration, demand era and buyer adoption via tech alliance and channel service associate ecosystem. He leads joint associate AI options to facilitate worth creation for purchasers. Previous to DataRobot, Chen was at IBM main inside AI initiatives.