Callum Macpherson

Callum Macpherson

Machine Learning

Posts by Tags

CI

Information Retrieval

LLM

LLMOPs

MLOPS

Continual Learning: Which metrics are important?

5 minute read

Published:

One of the most difficult things to identify throughout the lifecycle of a deployed machine learning model is: “when do I need to retrain my model?”. The most important thing is to use monitoring and observability to determine when a model is no longer performing well on offline data. The key questions you need to ask yourself as an ML Engineer are:

Red-teaming

Retrieval-augmented Generation (RAG)

continual learning

Continual Learning: Which metrics are important?

5 minute read

Published:

One of the most difficult things to identify throughout the lifecycle of a deployed machine learning model is: “when do I need to retrain my model?”. The most important thing is to use monitoring and observability to determine when a model is no longer performing well on offline data. The key questions you need to ask yourself as an ML Engineer are:

distribution drift

Continual Learning: Which metrics are important?

5 minute read

Published:

One of the most difficult things to identify throughout the lifecycle of a deployed machine learning model is: “when do I need to retrain my model?”. The most important thing is to use monitoring and observability to determine when a model is no longer performing well on offline data. The key questions you need to ask yourself as an ML Engineer are:

safety

text classification