Explore how REA Group rebuilt its data science pipeline to optimize data scientist autonomy in this 24-minute conference talk from YOW! 2019. Delve into the technical solutions and social challenges faced by engineering and data science teams as they worked to reduce the time from ideation to shipped product. Learn about REA's 5+ year history of using machine learning to segment and profile consumer intent, including determining if a user is likely a buyer, seller, renter, or investor. Gain insights from software engineer Justin Hamman and data enthusiast Jack Low as they share their experiences in building a scalable data science infrastructure. Discover recommended books on reinforcement learning, machine learning design patterns, and practical applications of AI in computer vision to further enhance your understanding of data science and machine learning concepts.
Overview
Syllabus
Building a Scalable Data Science Pipeline at REA • Justin Hamman & Jack Low • YOW! 2019
Taught by
GOTO Conferences