awesome-tech-rss VS feelskunaman

Compare awesome-tech-rss vs feelskunaman and see what are their differences.

awesome-tech-rss

List of awesome RSS channels related to startup, science and technology. (by tuan3w)

feelskunaman

A tool for visualizing emotions in music using a Python wrapper for Spotify API. Independent post-baccalaureate research by Nick Stapleton. For Kunaveer, a friend. (by nhstaple)
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SaaSHub - Software Alternatives and Reviews
SaaSHub helps you find the best software and product alternatives
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awesome-tech-rss feelskunaman
1 1
114 9
- -
3.2 1.6
26 days ago 11 months ago
Python Python
Creative Commons Zero v1.0 Universal -
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-tech-rss

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

feelskunaman

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

What are some alternatives?

When comparing awesome-tech-rss and feelskunaman you can also consider the following projects:

braindecode - Deep learning software to decode EEG, ECG or MEG signals

omnizart - Omniscient Mozart, being able to transcribe everything in the music, including vocal, drum, chord, beat, instruments, and more.

snntorch - Deep and online learning with spiking neural networks in Python

awesome-python - 📚 Awesome Python Resources (mostly PyCon).

awesome-cvelabs - A list of all awesome CVELabs

eyeloop - EyeLoop is a Python 3-based eye-tracker tailored specifically to dynamic, closed-loop experiments on consumer-grade hardware.