Presented By O'Reilly and Cloudera
Make Data Work
22–23 May 2017: Training
23–25 May 2017: Tutorials & Conference
London, UK

The business case for deep learning, Spark, and friends

Sanjay Mathur (Silicon Valley Data Science)
9:059:30 Tuesday, 23 May 2017
Data 101, Strata Business Summit
Location: Capital Suite 14
Level: Non-technical
Average rating: ***..
(3.80, 5 ratings)

Technologies like deep learning are white-hot, but why do they matter? The secret power of today’s data technologies is that they promote economic scaling and flexible development patterns that can adapt to business needs—but industry hype has obscured much of the value to those approaching the topic. Skepticism is an understandable reaction.

Developers are usually the first to understand why some technologies cause more excitement than others. Sanjay Mathur relates this insider knowledge, providing a tour through the hottest emerging data technologies of 2017 to explain why they’re exciting in terms of both new capabilities and the new economies they bring. Sanjay explores the emerging platforms of choice and explains where they fit into a complete data architecture and what they have to offer in terms of new capabilities, efficiencies, and economies of use.

Topics include:

  • Deep learning and AI
  • Spark
  • Docker and containers
  • Notebooks for data science
Photo of Sanjay Mathur

Sanjay Mathur

Silicon Valley Data Science

As the CEO and cofounder of Silicon Valley Data Science, Sanjay Mathur has brought together a team of world-class data scientists and engineers to help companies become more data driven. Previously, Sanjay was a partner in Accenture’s R&D organization, Accenture Technology Labs, where he led a global team that delivered market-ready business solutions built using emerging technologies to Accenture’s clients and built three different analytics and data practices, including the Information Insight R&D team focusing on machine learning and the semantic web, the Analytics and Insight group focused on predictive analytics, and the Data and Platforms R&D group focused on analytics, big data, and virtualization. He was also SVP of product for LiveOps, where he was responsible for LiveOps’s overall product strategy and roadmap and designed and deployed social, mobile, multichannel, and analytic applications into the LiveOps Cloud Platform.