Challenges faced in machine learning infrastructure in traditional large enterprises
Who is this presentation for?
- CIOs, CDOs, and heads of data science
The success of Web 2.0 companies like Google, Facebook, and Amazon is dependent on the usage of machine learning for their internal applications to increase revenue. The same holds true for the traditional large enterprises. However, in a large enterprise, machine learning is being done quite differently at large scale. Enterprises face a different set of challenges predominant because of their different infrastructure setup. Venkata Gunnu and Harish Doddi highlight some of the genuine challenges faced, key insights, and best practices that accelerate the machine learning models in the production environment.
- A basic understanding of machine learning models built for businesses
What you'll learn
- Understand machine learning infrastructure in large traditional enterprises
Venkata Gunnu is a senior director of data science at Comcast, where he manages data science and data engineering teams and architects data science projects that process and analyze billions of messages a day and petabytes of data. Venkata is a leader in data science democratization with 15+ years of data science modeling, design, architect, consultant, entrepreneur, and development experience, and 10+ years of that in data science modeling, big data and the cloud. He earned a master’s in information systems management in project planning and management from Central Queensland University, Australia. He has experience with product evangelization and speaking at conferences, user groups.
Harish Doddi is cofunder and CEO of Datatron. Previously, he held roles at Oracle; Twitter, where he worked on open source technologies, including Apache Cassandra and Apache Hadoop, and built Blobstore, Twitter’s photo storage platform; Snap, where he worked on the backend for Snapchat Stories; and Lyft, where he worked on the surge pricing model. Harish holds a master’s degree in computer science from Stanford, where he focused on systems and databases, and an undergraduate degree in computer science from the International Institute of Information Technology in Hyderabad.
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