makeZFS_armbian VS NAS-Projects

Compare makeZFS_armbian vs NAS-Projects and see what are their differences.

makeZFS_armbian

RockPro64 Based NAS setup guide with ZFS (by nathmo)
Nas

NAS-Projects

Automated deep learning algorithms implemented in PyTorch. [Moved to: https://github.com/D-X-Y/AutoDL-Projects] (by D-X-Y)
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makeZFS_armbian NAS-Projects
2 1
6 1,288
- -
10.0 9.4
over 1 year ago over 2 years ago
Python 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.

makeZFS_armbian

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

NAS-Projects

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

What are some alternatives?

When comparing makeZFS_armbian and NAS-Projects you can also consider the following projects:

AutoDL-Projects - Automated deep learning algorithms implemented in PyTorch.

autokeras - AutoML library for deep learning

archai - Accelerate your Neural Architecture Search (NAS) through fast, reproducible and modular research.

Hypernets - A General Automated Machine Learning framework to simplify the development of End-to-end AutoML toolkits in specific domains.

Movie_Data_Capture - Local Movies Organizer

nni - An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

AutoML - This is a collection of our NAS and Vision Transformer work. [Moved to: https://github.com/microsoft/Cream]