Executive Briefing: What it takes to use machine learning in fast data pipelines
Your team is building machine learning capabilities. Dean Wampler demonstrates how to integrate these capabilities in streaming data pipelines so you can leverage the results quickly and update them as needed and covers challenges such as how to build long-running services that are very reliable and scalable and how to combine a spectrum of very different tools, from data science to operations.
| Talk Title | Executive Briefing: What it takes to use machine learning in fast data pipelines |
| Speakers | Dean Wampler (Anyscale) |
| Conference | Strata Data Conference |
| Conf Tag | Making Data Work |
| Location | London, United Kingdom |
| Date | April 30-May 2, 2019 |
| URL | Talk Page |
| Slides | Talk Slides |
| Video | |
Dean Wampler helps you develop a conceptual understanding of the challenges faced by your teams as they develop and deploy machine learning and artificial intelligence services integrated with fast data (streaming) pipelines. While combining these technologies is challenging, the benefits include timely delivery of innovative services to your customers. Dean begins by briefly discussing machine learning use cases that are best delivered as streaming data applications. He then explores the main challenges faced when deploying these technologies together and outlines solutions to these challenges, including criteria to use when evaluating choices. Along the way, he explains the tools your teams are already talking about and the role they play. Topics include:
