Experiments in dispatching Metaflow flows to Flyte.
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Updated
Mar 26, 2022 - Python
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.
Using Metaflow for training a DL model with Tensorflow.
A recommender system for book recommendations developed within a production-ready workflow. This project utilizes Metaflow, AWS, and the Surprise library.
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.
An awesome list of machine learning relative system design blog posts from cool eng blogs
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
Fully functional Metaflow metadata service, UI and datastore deployment with docker and docker-compose.
Sentiment Analysis pipeline with SKLearn, Metaflow, AWS and GitHub CI
Get Yu-Gi-Oh! card recommendations by the magic of machine learning
Parallelizing ImageNet Training with Metaflow On Kubernetes
Metaflow On Kubernetes
Experimentation Of different deep learning models for classification of digits on a MNIST dataset using Metaflow
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