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Overview
Ready for information and practical experience in building advanced LLM applications using multi-stage reasoning LLM chains and agents? You’re in the right place. First, you’ll learn how to decompose a problem into its components and select the most suitable model for each step to enhance business use cases. Following this, we’ll show you how to construct a multi-stage reasoning chain utilizing LangChain and HuggingFace transformers. Finally, you’ll be introduced to agents and will design an autonomous agent using generative models on Databricks.
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Coming Soon...
Foundations of Compound AI Systems Defining Compound AI Systems Designing Compound AI Systems Deconstructing and Planning a Use Case Planning an AI System for Product Quality Complaints Building Multi-Stage Reasoning Chains Introduction to Multi-Stage Reasoning Chains Databricks Products for Building Multi-Stage Reasoning Systems Building Multi-Stage Reasoning Chains in Databricks Agents and Cognitive Architectures Introduction to Agents Tools for Building Agents Multi-Modal AI Agent Design in Databricks Creating a ReAct Agent
Foundations of Compound AI Systems
Building Multi-Stage Reasoning Chains
Agents and Cognitive Architectures
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