ML-Workspace
ML-For-Beginners
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| ML-Workspace | ML-For-Beginners | |
|---|---|---|
| 7 | 28 | |
| 3,324 | 66,806 | |
| 1.1% | 3.3% | |
| 2.7 | 8.0 | |
| 5 months ago | 13 days ago | |
| Jupyter Notebook | HTML | |
| Apache License 2.0 | 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.
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.
ML-For-Beginners
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Good coding groups for black women?
- https://github.com/microsoft/ML-For-Beginners
Also check out this list Pitt puts out every year:
- FLaNK Stack Weekly for 20 Nov 2023
- ML for Beginners GitHub
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is it worth learning NLP without master degree?
I don't recommend just jumping in into natural language processing directly without understanding artificial intelligence theory. I personally recommend for you to start with the basic stuff (regression, classification, and clustering, for example), and then jump into more advanced topics. You already know software developer stuff, so that's a big step already, and it should be easier to understand some concepts. Maybe follow Microsoft's machine learning for beginners curriculum? It looks like a good roadmap overall to not instantly burn out on nlp
- AI i Machine Learning
- I want to learn more about AI and Machine Learning
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Pocetak ML karijere
https://github.com/microsoft/ML-For-Beginners jel mislis na ovo?
- How could I have known
- GitHub - microsoft/ML-For-Beginners: 12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
- How do I reset my career after already getting my masters?
What are some alternatives?
JupyterLab - JupyterLab computational environment.
FLAML - A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.
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
lego-mindstorms - My LEGO MINDSTORMS projects (using set 51515 electronics)
keytotext - Keywords to Sentences
pycaret - An open-source, low-code machine learning library in Python
self-hosted - Sentry, feature-complete and packaged up for low-volume deployments and proofs-of-concept
Data-Science-For-Beginners - 10 Weeks, 20 Lessons, Data Science for All!
Code-Server - VS Code in the browser
pyVHR - Python framework for Virtual Heart Rate
cocalc-docker - DEPRECATED (was -- Docker setup for running CoCalc as downloadable software on your own computer)
S2ML-Art-Generator - Multiple notebooks which allow the use of various machine learning methods to generate or modify multimedia content [Moved to: https://github.com/justin-bennington/S2ML-Generators]