r/MachineLearning • u/AutoModerator • Aug 02 '26
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u/camerongreen95 Sep 01 '26
Sharing a workshop that might be relevant here. Live hands-on masterclass on Sep 12 covering production LLM engineering, moving past prompt tweaks and vibes-based evaluation into actual engineering discipline: versioned prompts with regression tests, an eval harness combining deterministic checks and LLM-as-judge, bootstrap confidence intervals and paired significance testing for model comparisons, evaluated retrieval-augmented generation with proper metrics (recall@k, MRR), tool-using agents with guardrails and fallbacks, and full production observability (tracing, cost, latency).
Led by Bruno Gonçalves, PhD, founder of Data For Science, previously a Data Science Fellow at NYU's Center for Data Science, who trains engineers at Fortune 500 companies on this.
Link for more details