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Airbnb Researchers Develop Chronon: A Framework for Developing Production-Grade Features for Machine Learning Models

Marktechpost

In the ever-evolving landscape of machine learning, feature management has emerged as a key pain point for ML Engineers at Airbnb. Airbnb recognized the need for a solution that could streamline feature data management, provide real-time updates, and ensure consistency between training and production environments.

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Introducing the Topic Tracks for ODSC East 2025: Spotlight on Gen AI, AI Agents, LLMs, & More

ODSC - Open Data Science

Topics Include: Agentic AI DesignPatterns LLMs & RAG forAgents Agent Architectures &Chaining Evaluating AI Agent Performance Building with LangChain and LlamaIndex Real-World Applications of Autonomous Agents Who Should Attend: Data Scientists, Developers, AI Architects, and ML Engineers seeking to build cutting-edge autonomous systems.

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Deliver your first ML use case in 8–12 weeks

AWS Machine Learning Blog

The first is by using low-code or no-code ML services such as Amazon SageMaker Canvas , Amazon SageMaker Data Wrangler , Amazon SageMaker Autopilot , and Amazon SageMaker JumpStart to help data analysts prepare data, build models, and generate predictions. He has a background in software engineering and AI research.

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ML Pipeline Architecture Design Patterns (With 10 Real-World Examples)

The MLOps Blog

Getting a workflow ready which takes your data from its raw form to predictions while maintaining responsiveness and flexibility is the real deal. At that point, the Data Scientists or ML Engineers become curious and start looking for such implementations. 1 Data Ingestion (e.g.,

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