gdelt VS awesome-production-machine-learning

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

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gdelt awesome-production-machine-learning
- 9
- 16,020
- 1.1%
- 7.5
- 1 day ago
BSD 3-clause "New" or "Revised" License 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.

gdelt

Posts with mentions or reviews of gdelt. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning gdelt yet.
Tracking mentions began in Dec 2020.

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.

What are some alternatives?

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

heidi - heidi : tidy data in Haskell

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

awesome-datascience - :memo: An awesome Data Science repository to learn and apply for real world problems.

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

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

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

datascience - Curated list of Python resources for data science.

awesome-mlops - :sunglasses: A curated list of awesome MLOps tools

awesome-ocr

seldon-core - An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models