sign_language_detector VS VevestaX

Compare sign_language_detector vs VevestaX and see what are their differences.

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sign_language_detector VevestaX
2 10
3 27
- -
0.0 0.0
almost 3 years ago over 1 year ago
Jupyter Notebook Jupyter Notebook
- Apache License 2.0
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.

sign_language_detector

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

VevestaX

Posts with mentions or reviews of VevestaX. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-05-12.

What are some alternatives?

When comparing sign_language_detector and VevestaX you can also consider the following projects:

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nlpaug - Data augmentation for NLP

MLOps - End to End toy example of MLOps

CameraTraps - PyTorch Wildlife: a Collaborative Deep Learning Framework for Conservation.

vertex-ai-samples - Sample code and notebooks for Vertex AI, the end-to-end machine learning platform on Google Cloud

Made-With-ML - Learn how to design, develop, deploy and iterate on production-grade ML applications.

mlflow-deployments - Source code for the post Effortless deployments with MLFlow, showcasing how logging models using MLFLow can provide you want to easily deploy them in production later.

mlflow-easyauth - Deploy MLflow with HTTP basic authentication using Docker

OAD - Collection of tools and scripts useful to automate microscopy workflows in ZEN Blue using Python and Open Application Development tools and AI tools.

recommenders - Best Practices on Recommendation Systems

bodywork-pymc3-project - Serving Uncertainty with Bayesian inference, using PyMC3 with Bodywork