azure-devops-python-api
recommenders
| azure-devops-python-api | recommenders | |
|---|---|---|
| 4 | 6 | |
| 545 | 18,019 | |
| 1.8% | 1.2% | |
| 3.7 | 9.5 | |
| 8 days ago | 5 days ago | |
| Python | Python | |
| MIT License | MIT License |
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.
azure-devops-python-api
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How do you navigate code when dealing with packages that return nested lists of custom objects for everything?
Examples: https://github.com/microsoft/azure-devops-python-api/blob/dev/azure-devops/azure/devops/_models.py
- Help extracting Work Items faster using Azure Devops API
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Is it possible to send complex commands with azure aks sdk?
Do you want to Azure DevOps Python API? Share more details to investigate this issue further. Learn how to call different APIs by viewing the samples in the Microsoft/azure-devops-python-samples repo. In addition, check the code examples about Python.
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Extract Capacities from ADO
For Python client library, refer to this link for more information.
recommenders
- My kernel dies when I fit my LightFm model from Microsoft Recommenders
- There is framework for everything.
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This Week in Python
recommenders – Best Practices on Recommendation Systems
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Input to SVD, SAR, NMF
I would like to do a benchmarking on the Microsoft models SVD, SAR and NMF (available here: https://github.com/microsoft/recommenders) but with this input data I get a precision and recall close to zero. Any ideas how I can improve this? For SVD and NMF (surprise library) the model wants a rating input that is normally distributed, which it not the case for my binary data where the transactions all have a rating of 1.
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Opinion on choice of model - Recommender System
Then I tried to find some more advanced models and I found this really good list and in there I found the Microsoft one. So it's' where we are now, which a bunch of different models and not a documentation/tutorials out there.
What are some alternatives?
azure-sdk-for-python - This repository is for active development of the Azure SDK for Python. For consumers of the SDK we recommend visiting our public developer docs at https://docs.microsoft.com/python/azure/ or our versioned developer docs at https://azure.github.io/azure-sdk-for-python.
metarank - A low code Machine Learning personalized ranking service for articles, listings, search results, recommendations that boosts user engagement. A friendly Learn-to-Rank engine
anonfile-api - An unofficial Python Anonfiles.com API
python-minecraft-clone - Source code for each episode of my Minecraft clone in Python YouTube tutorial series.
httpie - 🥧 HTTPie CLI — modern, user-friendly command-line HTTP client for the API era. JSON support, colors, sessions, downloads, plugins & more.
TensorRec - A TensorFlow recommendation algorithm and framework in Python.
lava - Microsoft Azure Exploitation Framework
pytorch-lightning - Build high-performance AI models with PyTorch Lightning (organized PyTorch). Deploy models with Lightning Apps (organized Python to build end-to-end ML systems). [Moved to: https://github.com/Lightning-AI/lightning]
azure-devops-python-samples - Python samples for interacting with and managing Azure DevOps
Google-rank-tracker - SEO: Python script + shell script and cronjob to check ranks on a daily basis
nutter - Testing framework for Databricks notebooks
horapy - 🐍 Python bidding for the Hora Approximate Nearest Neighbor Search Algorithm library