InfoQ Homepage Presentations Simplifying ML Workflows with Apache Beam
Simplifying ML Workflows with Apache Beam
Summary
Tyler Akidau discusses how Apache Beam is simplifying pre- and post-processing for ML pipelines.
Bio
Tyler Akidau is a senior staff software engineer at Google, where he is the technical lead for the Data Processing Languages & Systems group, responsible for Google's Apache Beam efforts, Google Cloud Dataflow, and internal data processing tools like Google Flume, MapReduce, and MillWheel. His also a founding member of the Apache Beam PMC.
About the conference
QCon.ai is a AI and Machine Learning conference held in San Francisco for developers, architects & technical managers focused on applied AI/ML.
This content is in the AI, ML & Data Engineering topic
Related Topics:
Sponsored Content
-
Related Editorial
-
Related Sponsors
-
Popular across InfoQ
-
AWS Introduces ECS Managed Instances for Containerized Applications
-
GitHub Introduces New Embedding Model to Improve Code Search and Context
-
Google DeepMind Introduces CodeMender, an AI Agent for Automated Code Repair
-
OpenAI Adds Full MCP Support to ChatGPT Developer Mode
-
Paper2Agent Converts Scientific Papers into Interactive AI Agents
-
Mental Models in Architecture and Societal Views of Technology: A Conversation with Nimisha Asthagiri
-