At DataRobot, we’re dedicated to serving to our clients maximize the worth they acquire from our AI Platform. Right this moment, we’re excited to share that DataRobot has joined the Amazon SageMaker Prepared Program. This designation helps clients uncover associate software program options which are validated by Amazon Net Providers (AWS) Companion Options Architects to combine with Amazon SageMaker. Our associate ecosystem is a key driver in guaranteeing buyer success, and partnering with AWS supplies clients with deep integrations that amplify the productiveness of knowledge science groups.Â
DataRobot and SageMaker create a robust duo to speed up AI adoption Â
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 robotically accumulate and monitor inference metrics. Monitoring jobs might be scheduled natively from DataRobot with out the effort of handbook 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 gives out-of-the-box governance greatest practices equivalent to automated mannequin compliance documentation and mannequin versioning so all DataRobot and SageMaker fashions might be ruled centrally.Â
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 Companion, and look ahead to serving to corporations obtain their expertise targets by leveraging AWS. To study extra about DataRobot’s integration with Amazon SageMaker, obtain the whitepaper right here.
Concerning the SageMaker Prepared Program
Becoming a member of the Amazon SageMaker Prepared Program differentiates DatRobot as an AWS Companion Community (APN) member with a product that works with Amazon SageMaker and is mostly obtainable for and absolutely helps AWS clients. The Amazon SageMaker Prepared program helps clients rapidly 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 supplies.Â
Amazon SageMaker gives a sturdy set of capabilities and AWS Companions add worth to additional increase the capabilities by integrating with their options. By offering clients a catalog of Software program Path associate options that elevate 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 clients Amazon SageMaker-supported merchandise that supply Amazon SageMaker each in Software program Path Companion options they already know, or supply merchandise that simplify every step of the ML mannequin constructing. These functions are validated by AWS Companion Options Architects to make sure clients 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 clients establish 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 overview the Amazon SageMaker Prepared Companion 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 growth wants.Â
Concerning the writer
Ksenia Chumachenko is a Vice President of Alliances and Enterprise Improvement at DataRobot. She leads Cloud and Know-how Alliances international workforce, serving to purchasers get worth from AI by a wider Cloud and Information ecosystem.
Ksenia has greater than 20 years of expertise delivering technological options and growing associate ecosystems throughout product startups, ISVs, and system integrators. She has ardour for taking partnerships to the subsequent degree by way of collaboration, creativity, data-driven strategy, and workforce nurturing with profitable expertise in establishing associate channel and constructing groups in pre- and post-IPO knowledge startups.
Ksenia holds an MBA in World Enterprise and Entrepreneurship from NYU Stern Faculty 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 Companion Information Science at DataRobot, the place he drives product integration, demand era and buyer adoption by 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 inner AI initiatives.
