awesome-production-machine-learning VS awesome-mlops

Compare awesome-production-machine-learning vs awesome-mlops and see what are their differences.

awesome-production-machine-learning

A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning (by EthicalML)
Machine Learning Mlops Interpretability explainability responsible-ai Deep Learning machine-learning-operations ml-ops ml-operations privacy-preserving privacy-preserving-ml privacy-preserving-machine-learning Data Mining large-scale-ml production-ml large-scale-machine-learning production-machine-learning Awesome awesome-list
Source Code
ethical.institute
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awesome-mlops

:sunglasses: A curated list of awesome MLOps tools (by kelvins)
Awesome Machine Learning machine-learning-engineering mle Mlops Data Science ML AI
Source Code
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awesome-production-machine-learning awesome-mlops
9 7
15,947 3,575
2.1% -
7.4 6.8
8 days ago 19 days ago
Python
MIT License -
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

awesome-production-machine-learning

Posts with mentions or reviews of awesome-production-machine-learning. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-12-13.

awesome-mlops

Posts with mentions or reviews of awesome-mlops. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-11-20.

What are some alternatives?

When comparing awesome-production-machine-learning and awesome-mlops you can also consider the following projects:

shap - A game theoretic approach to explain the output of any machine learning model.

awesome-mlops - A curated list of references for MLOps

awesome-jax - JAX - A curated list of resources https://github.com/google/jax

kserve - Standardized Serverless ML Inference Platform on Kubernetes

netron - Visualizer for neural network, deep learning and machine learning models

BentoML - The most flexible way to serve AI/ML models in production - Build Model Inference Service, LLM APIs, Inference Graph/Pipelines, Compound AI systems, Multi-Modal, RAG as a Service, and more!

awesome-ml-for-cybersecurity - :octocat: Machine Learning for Cyber Security

metaflow - :rocket: Build and manage real-life ML, AI, and data science projects with ease!

datascience - Curated list of Python resources for data science.

kubeflow-learn

awesome-ocr

kind - Kubernetes IN Docker - local clusters for testing Kubernetes

awesome-production-machine-learning vs shap awesome-mlops vs awesome-mlops awesome-production-machine-learning vs awesome-jax awesome-mlops vs kserve awesome-production-machine-learning vs netron awesome-mlops vs BentoML awesome-production-machine-learning vs awesome-ml-for-cybersecurity awesome-mlops vs metaflow awesome-production-machine-learning vs datascience awesome-mlops vs kubeflow-learn awesome-production-machine-learning vs awesome-ocr awesome-mlops vs kind