AI & DEEP LEARNING
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Date: July 24, 2019
Time: 11:00am – 12:00am PT
Duration: 1 hour

Run on NVIDIA GPUs, H2O Driverless AI empowers data scientists at Deserve to tackle larger data sets, iterate faster, and tune models to maximize prediction accuracy and business value. It brings game-changing performance to some of the most difficult data science and machine learning workflows so that financial firms can reduce time spent waiting to get the most valuable insights and accelerate returns on investment. Deserve, a Silicon Valley startup, uses H2O Driverless AI to determine a more holistic credit scoring model based on an applicant’s full financial picture, considering factors like how they manage money, along with records of on-time payments, to predict future credit potential.

In this webinar, you’ll learn how to:
  • Personalize credit scoring models with AI
  • Get quicker results using Driverless AI on NVIDIA GPUs
  • Save time, resulting in consumer satisfaction, loyalty, and a long-term credit relationship


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DGX Station Datasheet

Get a quick low-down and technical specs for the DGX Station.
DGX Station Whitepaper

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.

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Speakers

Yan Yang

Data Engineer and Scientist, Deserve

Yan has industrial experiences with design and implementation of large-scale data platform, including analytic application development, Hadoop and Spark computation frameworks and integration, ETL and data pipelines. He has a PhD in Computational Engineering with a focus in empirical data modeling and statistical analysis.

Vinod Iyengar

VP of Data Science Transformation, H20.ai

Vinod is the VP of marketing and technical alliances at H2O.ai. He leads all product marketing efforts, new product development and integrations with partners. Vinod comes with over 10 years of Marketing & Data Science experience in multiple startups. He was the founding employee for his previous startup, Activehours (Earnin), where he helped build the product and bootstrap the user acquisition with growth hacking. He has worked to grow the user base for his companies from almost nothing to millions of customers. He’s built models to score leads, reduce churn, increase conversion, prevent fraud and many more use cases.

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Date & Time: Wednesday, April 22, 2018