Show HN: ML model to tell if you were naughty this year
https://mlem-nice-or-naughty.fly.dev/
And a blog post about it - please enjoy! https://medium.com/@mike0sv/i-trained-a-model-to-tell-if-you...
aguschin
Re:I trained a model to tell if you were naughty this year
on Friday December 23, 2022 @12:24PM (#34108339)
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 :)
Re:Show HN: MLEM – ML model deployment tool
on Wednesday June 01, 2022 @12:07PM (#31583976)
Oh, and MLEM can also serialize any Python function. (How could I forget!)
Re:Show HN: MLEM – ML model deployment tool
on Wednesday June 01, 2022 @11:58AM (#31583819)
Yep! Machine Learning should be mlemming :)
Re:Show HN: MLEM – ML model deployment tool
on Wednesday June 01, 2022 @11:57AM (#31583795)
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)
Re:Show HN: MLEM – ML model deployment tool
on Wednesday June 01, 2022 @11:18AM (#31583109)
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!
Re:Show HN: MLEM – ML model deployment tool
on Wednesday June 01, 2022 @11:15AM (#31583059)
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.
Show HN: MLEM – ML model deployment tool
Hi, I'm one of the project creators. MLEM is a tool that helps you deploy your ML models. It’s a Python library + Command line tool.1. MLEM can package an ML model into a Docker image or a Python package, and deploy it to, for example, Heroku.2. MLEM saves all model metadata to a human-readable text file: Python environment, model methods, model input & output data schema and more.3. MLEM...