NVIDIA WEBINAR
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Data science gives enterprises the power to analyze and optimize business processes, supply chains and digital experiences. But data preparation and machine learning workloads typically take a long time. In cases when time is of the essence, such as predicting demand for perishable goods, being able to speed up data science workflows is a significant advantage.
With RAPIDS, a new set of open-source libraries for GPUs, data scientists can accelerate their python toolchain with minimal code changes and drastically improve productivity, while achieving top-model accuracy.
- What RAPIDS is and the key benefits for you
- How to get started with RAPIDS to accelerate machine learning workflows
- Why NVIDIA DGX-2, with 512 GB memory and 10,240 Tensor Cores, is the perfect tool to reap the benefits of accelerated data science workloads
- Use cases from industries such as Retail, Finance and Research
ONDEMAND WEBINAR REGISTRATION
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DGX Station Whitepaper
Dive deeper into the DGX Station and learn more about the architecture, NVLink, frameworks, tools and more.
Dive deeper into the DGX Station and learn more about the architecture, NVLink, frameworks, tools and more.
DGX Station Whitepaper
Dive deeper into the DGX Station and learn more about the architecture, NVLink, frameworks, tools and more.
Dive deeper into the DGX Station and learn more about the architecture, NVLink, frameworks, tools and more.
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Speaker
John Harding
EMEA Financial Services Industry Lead, NVIDIA
John started his career in the Financial Services sector with Sun Microsystems, managing global relationships with JP Morgan & Bank of America. He went on to spend 10 years at NetApp, leading global FSI teams and then two years at Juniper Networks, as EMEA Sales Director for FSI. Today, he is responsible for NVIDIA's FSI business in EMEA, along with the newly announced RAPIDS machine learning business in EMEA.
Miguel Martínez
Deep Learning Solution Architect, NVIDIA
Miguel Martínez is a Deep Learning Solution Architect at NVIDIA, where he concentrates on RAPIDS. Previously, he mentored students at Udacity's Artificial Intelligence Nanodegree. He has a strong background in financial services, mainly focused on payments and channels. As a constant and steadfast learner, he is always up for new challenges.
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