MLOps Live Webinar Series - Call for Speakers

MLOps Live is a complimentary webcast focusing on managing and automating machine learning pipelines to bring data science into real business applications. The sessions go beyond theory, with industry leaders sharing challenges and practical solutions through real case studies that involve running AI experiments at scale, versioning, delivery to production, reproducibility and data access.​

Suggested Topics:

• Open-source technologies for MLOps

• KubeFlow standardization

• MLRun

• MLFlow

• Online and offline feature stores

• Experiment and data tracking

• Reinforced machine learning

• AI use-cases in business applications

• Machine learning deployment and operation challenges

• Machine learning model training at scale

• Machine learning pipeline automation

• Serverless in machine learning pipelines

• Model deployment and monitoring in production

• Implementing AI in real-time and interactive applications

• Model versioning and reproducibility

• Data and feature vector access in production

• Security challenges in production

• Using GPUs to accelerate training and inferencing

• Working in heterogeneous environments (multi-cloud, edge, on-premises)

• Distributed machine learning

• Spark and big data over Kubernetes

• Natural language processing at scale

• Cost optimization of machine learning pipelines