In this session, we present our experimental approach to creating DPK pipelines using agentic workflows. We will begin with a brief introduction to agentic workflows, followed by a walkthrough of two notebooks developed to support this work: The first notebook shows a planner agent for Data-Prep-Kit tasks with code generation. The agent builds DPK pipeline that performs required tasks defined by a natural language. The second notebook demonstrates how DPK transformers can be wrapped as tools within LangChain and LlamaIndex, along with examples of executing the transforms directly.
talk-data.com
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Speaker
Mohammad Nassar
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talks
Cloud Research Engineer
IBM Haifa
Mohammad Nassar, a Cloud Research Engineer at IBM Haifa, specializes in AI-driven data engineering, automation, and hybrid cloud technologies. With an M.Sc. in Computer Science from Technion, his research focused on coding theory and data systems. His work spans AI-powered data preparation, automation pipelines, and large-scale cloud solutions. Passionate about innovation, he also develops mobile applications, blending AI and user engagement.
Bio from: [AI Alliance] Simplifying DPK Pipeline Creation with Agentic Workflows
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