🚀 Metadata tracking and UI service for Metaflow!
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Updated
Sep 3, 2024 - Python
🚀 Metadata tracking and UI service for Metaflow!
Joining the modern data stack with the modern ML stack
Recommendations at "Reasonable Scale": joining dataOps with recSys through dbt, Merlin and Metaflow
Render Jupyter Notebooks With Metaflow Cards
Experiments in dispatching Metaflow flows to Flyte.
Tools for setting up and running pipelines in a Data Analytics and Production System (DAPS).
Zephyr is a command-line utility that provides project and component scaffolding to build modular pipelines.
Leverage Metaflow, PyTorch, AWS S3, Elasticsearch, FastAPI and Docker to create a production-ready facial recognition solution. It demonstrates the practical use of deep metric learning to recognize previously unseen faces without prior training.
Using Metaflow for training a DL model with Tensorflow.
Fully functional Metaflow metadata service, UI and datastore deployment with docker and docker-compose.
A pipeline built on MetaFlow for training Fashion MNIST dataset using Pytorch, experiment tracking using MLFlow and model deployment using BentoML
MalaysianPayGap LLM using LocalGPT
Sentiment Analysis pipeline with SKLearn, Metaflow, AWS and GitHub CI
Get Yu-Gi-Oh! card recommendations by the magic of machine learning
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