MLOps on Streaming Platform by Sushma Gudimalla

Join us for an enlightening session led by Sushma Gudimalla, an expert in MLOps and streaming technologies, as we delve into the integration of Machine Learning Operations (MLOps) within streaming platforms. This meetup is designed for data scientists, ML engineers, DevOps professionals, and anyone interested in the dynamic field of real-time data processing and machine learning.

Event Overview:
In today's fast-paced digital landscape, the ability to process and analyze data in real time is invaluable. Streaming platforms enable continuous data ingestion and analysis, but integrating robust machine learning models into these platforms presents unique challenges and opportunities. Sushma Gudimalla will guide us through the critical aspects of implementing MLOps practices in streaming environments to ensure efficient, scalable, and reliable ML deployments.

What You Will Learn:

• Fundamentals of Streaming Platforms: An introduction to the architecture and components of popular streaming platforms like Apache Kafka, Apache Flink, and AWS Kinesis.
• Challenges in Real-Time ML Deployment: Discuss the specific challenges faced while deploying machine learning models in a streaming context, including latency, model updating, and data drift.
• MLOps Strategies for Streaming: Best practices and strategies for applying MLOps principles in streaming platforms, ensuring continuous integration and deployment (CI/CD), model monitoring, and automated model retraining.
• Tools and Technologies: Overview of tools and frameworks that support MLOps on streaming platforms, including TensorFlow Extended (TFX), MLflow, and Kubeflow.
• Real-World Case Studies: Insights into successful case studies where MLOps has been effectively implemented on streaming platforms, highlighting the lessons learned and outcomes achieved.

Who Should Attend:
This workshop is ideal for professionals and enthusiasts eager to understand how to seamlessly integrate machine learning workflows with real-time data processing platforms. Whether you are an experienced practitioner or a newcomer to the field, this session will equip you with the knowledge and skills to enhance your projects with the power of MLOps in streaming environments.

Come and join Sushma Gudimalla for this interactive and practical session to elevate your understanding of MLOps in the context of streaming platforms. Don’t miss this opportunity to network with peers and gain insights that could transform your approach to machine learning in real-time data environments!

We look forward to seeing you there and exploring the innovative world of MLOps on streaming platforms together!