Machine learning is on e of the biggest IT buzzwords today that has yet to show promise. Thou gh still a few years away, CIOs and IT execs are putting stock in the poten tial benefits it has to offer. According to a late 2017 survey conducted by ServiceNow, in conjunction with Oxford Ec onomics, 89% of companies have deployed machine learning o r are planning to deploy it. With ambitions and IT dollars going towards im plementation, how can organizations begin reaping the benefits of gaining b usiness value from machine learning as soon as possible?
\nIn this se ssion, Steve Wilkes, co-founder and CTO of Striim, will discuss how combini ng machine learning models with streaming data can enable companies to gain real-time predictions. Steve will go into detail on streaming integration and how it’s a key tenant for organizations in developing machine lea rning initiatives.
\nAudience members will receive insights on how or ganizations can best achieve operationalizing machine learning by:
\n\n Building Your ML Model - Collect data to train a mode l, and use it in a streaming fashion to perform real-time anomaly detection and predictions.\n Moving Data Preparation More Upstream - Data engineer s should involve data scientists earlier in the data acquisition process in order to simplify the operation of machine learning by ensuring data strea ms are in the same format as training files.\n ML and Streaming Integration Use Case - Steve will sh owcase a real-world example of how a company can compare streaming data aga inst a trained ML model.\n\n DTSTART:20181010T095000 SUMMARY:Stream Processing: The Secret Sauce for Operationalizing Machine Le arning DTEND:20181010T104959 LOCATION: See Description END:VEVENT END:VCALENDAR