rMsync
interactive_tutorials
| rMsync | interactive_tutorials | |
|---|---|---|
| 2 | 1 | |
| 90 | 85 | |
| - | - | |
| 0.0 | 6.6 | |
| almost 2 years ago | 27 days ago | |
| Jupyter Notebook | Jupyter Notebook | |
| GNU General Public License v3.0 only | - |
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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.
rMsync
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Google Drive Workflow
I got the closest with rMsync but the each notebook on my rM was fragmented into the PDF plus 2 metadata files, which made them pretty useless. So at best I might be able to achieve 1 way sync but once it's edited on the rM it needs to be exported as PDF. Some tools do exist to convert back to PDF but I haven't worked them out yet.
- Is there a way to automatically sync to Google Drive?
interactive_tutorials
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Google open-sources their graph mining library
For those wanting to play with graphs and ML I was browsing the arangodb docs recently and I saw that it includes integrations to various graph libraries and machine learning frameworks [1]. I also saw a few jupyter notebooks dealing with machine learning from graphs [2].
Integrations include:
* NetworkX -- https://networkx.org/
* DeepGraphLibrary -- https://www.dgl.ai/
* cuGraph (Rapids.ai Graph) -- https://docs.rapids.ai/api/cugraph/stable/
* PyG (PyTorch Geometric) -- https://pytorch-geometric.readthedocs.io/en/latest/
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1: https://docs.arangodb.com/3.11/data-science/adapters/
2: https://github.com/arangodb/interactive_tutorials#machine-le...
What are some alternatives?
Rhythm-Finder - ML-powered Music Recommendation Engine
danbooru - A taggable image board written in Rails.
rmfakecloud - host your own cloud for the remarkable
QuantumKatas - Tutorials and programming exercises for learning Q# and quantum computing
NetworkX - Network Analysis in Python
evidently - Evaluate and monitor ML models from validation to production. Join our Discord: https://discord.com/invite/xZjKRaNp8b
Human-pose-estimation - A quick tutorial on multi-pose estimation with OpenCV, Tensorflow and MoveNet lightning.
graph-mining
PyCBC-Tutorials - Learn how to use PyCBC to analyze gravitational-wave data and do parameter inference.