aguschin

3 karma · joined May 24, 2022

Developer and Product Engineer at Iterative.ai

aguschin··on I trained a model to tell if you were naughty this year

LOL, just was submitting the same link and got here. Was too late to publish first)

Anyway, I'm one of the authors - the other one published the blog post on medium. Hope this will give you some Christmas mood :)

aguschin··on Show HN: MLEM – ML model deployment tool

Oh, and MLEM can also serialize any Python function. (How could I forget!)

aguschin··on Show HN: MLEM – ML model deployment tool

Yep! Machine Learning should be mlemming :)

aguschin··on Show HN: MLEM – ML model deployment tool

Thank you! MLEM already supports Scikit-learn, PyTorch, XGBoost, LightGBM and CatBoost now. We're going to add fastai, TensorFlow and Huggingface very soon, and then there are many others we'd like to support! Feel free to post an issue in the GH repo for the framework of your choice)

aguschin··on Show HN: MLEM – ML model deployment tool

Thanks! We're going to add AWS Sagemaker, pure Kubernetes and Seldon-core soon. Feel free to drop an issue in GH if you need something in particular!

aguschin··on Show HN: MLEM – ML model deployment tool

Hi! Thanks for the question! There are a few important differences:

- MLEM automatically extracts the metadata from the model for you. With MLflow, you need to specify ML framework and environment.

- For the Model Registry that you can build in Git with MLEM, you don't need a separate service and Database up, except for GitHub or GitLab.