Real-Time Machine Learning: Features and Inference - MLOps Podcast #135

Explore the intricacies of real-time machine learning in this 52-minute podcast episode featuring Sasha Ovsankin and Rupesh Gupta, tech leaders from LinkedIn. Delve into the challenges and benefits of transitioning from batch to near real-time ML, covering topics such as real-time inference, feature engineering, and the tools and steps required for implementation. Gain insights on when to make this transition, the importance of feedback loops, and the technical details behind integrating recent information into models. Learn about embedding vector search, the true meaning of "real-time" in ML contexts, and the scenarios where real-time features are most beneficial. Discover the successes and learnings from implementing real-time features at LinkedIn, and understand the often-overlooked aspects of real-time ML. This comprehensive discussion provides valuable knowledge for ML practitioners looking to enhance their systems' responsiveness and effectiveness.