Large Language Model Operations (LLMOps) Explained

[@samsonv9332]

Martin, you have a knack to explain things that matter in a lucid/succinct manner in under 5-10 mins 🙏🏼🔥 Another fantastic video and a required dose for my LLM skills enhancement & journey, thank you for finding time to create these educational videos! I never miss your videos! 🙏🏼

[@achen94]

I feel like the MLops section in this video isn’t quite accurate? MLOps still encompasses fine tuning, model inference, etc. why are those absent from the MLOPs section and only found in LLM Ops?

[@Tony-dp1rl]

I had some LL Mops back when I cleaned floors for a living.

[@muskan3697]

😆

[@Beloved_Digital]

I love your contents 😊. They're are classical and unique

[@kevinb4006]

This is great content! I am curious, Does IBM leverage using the R programming language for data analysis, machine learning, etc? If so, can you explain how it is being used and why?

[@vdpoortensamyn]

ROGUE or ROUGE? ROUGE ( Recall-Oriented Understudy for Gisting Evaluation ) consists of a set of metrics that are used to compare the quality of a generated text against a reference text. It can be used whenever we have a reference text available. Some of the most common applications are: translations, text summarization, or entity extraction between others. The LLM has probably gone rogue when hallucinating! 😉

[@vineetdhyani9654]

Great

[@seanurquhart3179]

1 Video down. 3.4 million to go for your teaching goal.

[@sk3ffingtonai]

👏👏