Case Study: Driving Innovation with Machine Learning in the Enterprise

Presented by

Lynn Calvo, AVP Emerging Data Technology, GM Financial; Nick Chang, Head of Customer Success, BlueData

About this talk

Watch this on-demand webinar for a case study with GM Financial on deploying Machine Learning and Deep Learning applications using a flexible container-based architecture. GM Financial, the wholly-owned captive finance subsidiary of General Motors, is a global enterprise in a highly regulated industry. Learn about their journey in implementing Machine Learning, Deep Learning, and Natural Language Processing – including how they’ve kept up with the blistering pace of change, while delivering immediate value and managing costs. In this webinar, GM Financial will discuss some of their challenges, technology choices, and initial successes: - Addressing a wide range of Machine Learning use cases, from credit risk analysis to improving customer experience - Implementing multiple different tools (including TensorFlow™, Apache Spark™, Apache Kafka®, and Cloudera®) for different business needs - Deploying a multi-tenant hybrid cloud environment with containers, automation, and GPU-enabled infrastructure Don’t miss this webinar! Gain insights from an enterprise case study, and get perspective on Kubernetes® and other game-changing technology developments.

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Hewlett Packard Enterprise (HPE) is transforming how enterprises deploy AI / Machine Learning (ML) and Big Data analytics. HPE’s container-based software platform makes it easier, faster, and more cost-effective for enterprises to innovate with AI / ML and Big Data technologies – either on-premises, in the public cloud, or in a hybrid architecture. With HPE, our customers can spin up containerized environments within minutes, providing their data scientists with on-demand access to the applications, data, and infrastructure they need.