Session Details
Intelligent Experimentation using Machine Learning
Presentation
Experimentation is the standard to measure the impact of products we are building. From front-end UI changes to backend changes, the data-driven decisions to pick a winning variant is facilitated by our experimentation platform. In this talk, we share how we leveraged Machine Learning to invigorate our platform with the intelligence to dynamically adapt to changing product requirements.
The Speaker(s)
Nisha Bhaskaran
Nisha (https://scholar.google.com/citations?user=_f_2E5cAAAAJ&hl=en) is a senior software engineer at PayPal working on building the next-generation analytics and experimentation platform. She is a passionate technologist with an academic background and industry experience in AI/Machine Learning. In her career spanning over 8+ years, she has significant experience in building and deploying ML models and systems to production. She has experience with big data systems like Spark, Hadoop and has recently ventured into streaming with Kafka, Spark etc. She has worked in search and ranking for e-commerce, customer insights domain and is currently involved in building intelligent products for PayPal’s experimentation platform. She has presented her master’s thesis Lie to Me: Deceit Detection via Online Behavioral Learning in IEEE conference on Automatic Face and Gesture Recognition in 2011.
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