Stream Processing Meets Machine Learning: An Apache Flink Workshop

In today’s fast-paced data world, real-time processing is essential for instant insights. This hands-on session dives into Apache Flink, a powerful open-source stream processing framework, guiding participants through setting up a development environment and building real-time streaming applications. Going beyond stream processing, we’ll explore integrating machine learning with Flink using the Deep Java Library (DJL) for real-time inference. Attendees will work with Apache Kafka, apply transformations, manage stateful processing, and deploy ML models for tasks like real-time classification—gaining practical skills to enhance data-driven decision-making.

Key Takeaways:

• Master the fundamentals of Apache Flink for real-time stream processing.
• Learn to integrate machine learning models into Flink pipelines using Deep Java Library (DJL).
• Explore techniques for real-time inference and predictive analytics on streaming data.
• Gain hands-on experience with Kafka integration, state management, and end-to-end Flink workflows.

Tulika Bhatt embarked on her professional journey at Verizon, empowering customers with self-service tools and laying the groundwork for a career defined by innovation. With nearly a decade of diverse experience, including pivotal roles at BlackRock developing financial applications, Tulika transitioned to Netflix. In her current role in the Personalization space, she curates datasets to enhance content recommendations for over 250 million plus subscribers, managing trillions of data points annually. This experience has sharpened her ability to derive actionable insights from complex datasets, amplifying her impact on user experiences. Tulika actively contributes to industry knowledge through speaking engagements and articles, reflecting her passion for data-driven innovation in digital media. You can reach her on LinkedIn.