Bio

Vitaly has been designing data-centric systems for last 20 years and have gained huge experience in Data Science platforms. During 5 years he was involved as a Solution Architect in Cloud Data projects and have adopted different innovative approaches for Fast Data Processing and Machine Learning. At the moment my responsibility is leading Data and Analytics Centre of Excellence and building expertise in cloud data services.

Engineering a project accelerator for enterprise ML platforms, using Databriks, Kubernetes and Kafka

Data Engineering & MLOps

  • Session Language |English
"During the session we will review a case of building accelerator for ML platforms in Azure cloud. We will cover core components and technologies, such as, Databricks, Kafka and Kubernetes and focus in details on differences between popular MLOps platforms: Kubeflow vs MLFlow vs Neptune. Will discover approaches for designing the accelerator architecture and use cases in enterprise PROD environments.Content: 1. Case Study of ML project acceleration 2. Production ML platform: Databriks, Kafka, Kubernetes 3. Kubeflow vs MLFlow vs Neptune 4. Accelerator architecture and automated deployment to cloud 5. Demo: MLOps from training to deployment 6. Future of ML platform accelerators"

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