linear-tree
ML-Workspace
linear-tree | ML-Workspace | |
---|---|---|
3 | 7 | |
323 | 3,324 | |
- | 0.4% | |
0.0 | 2.7 | |
11 months ago | 6 months ago | |
Jupyter Notebook | Jupyter Notebook | |
MIT License | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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linear-tree
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Is there any algorithm that combines decision trees with regression models?
Sure is! Hereโs an implementation
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Running a randomforest on residuals from a ridge linear model in scikit learn
Check out https://github.com/cerlymarco/linear-tree
- GitHub - cerlymarco/linear-tree: A python library to build Model Trees with Linear Models at the leaves.
ML-Workspace
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[D] I recently quit my job to start a ML company. Would really appreciate feedback on what we're working on.
Also check out: https://github.com/ml-tooling/ml-workspace, it a nice open source project with lots of packages ready to use.
- ML-Workspace
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Coding for machine learning on Tab S8?
The other option - no reason why you couldn't host something on the desktop machine - web based IDE like R-Studio or Python - have a look at ml-workspace - https://github.com/ml-tooling/ml-workspace that runs in Docker and would provide interfaces for both Python and R, VSCode as well as a GPU accelerated variant for doing Tensorflow etc - either Windows or Linux can support Docker containers (Linux is less trouble apparently - I only have played with it in Linux personally)
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Dynamically spin up VM (based on specific HTTPS request) and stop it once session is over?
It will be a web based IDE dev kit (like Jupyter Hub, or JupyterLab) if you are familiar with them)
- All-in-One Docker Based IDE for Data Science and ML
- Visual Studio Code now available as Web based editor for GitHub repos
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[P] Install or update CUDA, NVIDIA Drivers, Pytorch, Tensorflow, and CuDNN with a single command: Lambda Stack
I'll stick with https://github.com/ml-tooling/ml-workspace, is a docker with all tools installed, also the option of using GPU, so I think is better than only for debian. This way anyone can use it.
What are some alternatives?
eli5 - A library for debugging/inspecting machine learning classifiers and explaining their predictions
JupyterLab - JupyterLab computational environment.
imodels - Interpretable ML package ๐ for concise, transparent, and accurate predictive modeling (sklearn-compatible).
Gitpod - DEPRECATED since Gitpod 0.5.0; use https://github.com/gitpod-io/gitpod/tree/master/chart and https://github.com/gitpod-io/gitpod/tree/master/install/helm
python-machine-learning-book-3rd-edition - The "Python Machine Learning (3rd edition)" book code repository
keytotext - Keywords to Sentences
FLAML - A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.
self-hosted - Sentry, feature-complete and packaged up for low-volume deployments and proofs-of-concept
dtreeviz - A python library for decision tree visualization and model interpretation.
Code-Server - VS Code in the browser
BigFivePersonality - The current project provides a Machine Learning trained model that is able to classify the trait with maximum value of the Big Five Personality Test, given the answers of this one.
cocalc-docker - DEPRECATED (was -- Docker setup for running CoCalc as downloadable software on your own computer)