arrow_back Applied Machine Learning for realtime #FairPlay against Fraud
Doing Data Science on Cloud arrow_forward
Build intelligent, real-time applications using Machine Learning
Submitted by Jayesh Sidhwani (@jayeshsidhwani) on Tuesday, 14 November 2017
Section: Full talk Technical level: Intermediate
The surge in the availability of large datasets, processing powers and the ability to process the data in real-time has opened up a plethora of opportunities in which Machine Learning algorithms can harness this power to build intelligent, real-time applications.
This talk will focus on how can we apply Machine Learning models to streaming data in real-time to derive insights.
- Discuss the current-state-of-affairs for deploying Machine Learning models
- Discuss shortcomings of this approach
- Discuss the value of streaming data
- Brief introduction to Apache Kafka and Streaming applications
- Discuss how to use Apache Kafka to use ML models in real-time
- Demonstrate how we use a Demography Prediction model in real-time
Jayesh leads the Personalisation team at Hotstar. He has been building streaming applications using Apache Kafka for the last 4 years. At Hotstar, the personalisation team builds Machine Learning models for its 150 million users and delivers it real-time. He can be reached on Twitter at @jayeshsidhwani