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Tools range from dataplatforms to vector databases, embedding providers, fine-tuning platforms, promptengineering, evaluation tools, orchestration frameworks, observability platforms, and LLM API gateways. The quality and structure of prompts significantly influence LLMs’ output.
Stefan is a software engineer, data scientist, and has been doing work as an ML engineer. He also ran the dataplatform in his previous company and is also co-creator of open-source framework, Hamilton. As you’ve been running the ML dataplatform team, how do you do that? Datadrift.
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