Gather-Deployment
ML-Workspace
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| Gather-Deployment | ML-Workspace | |
|---|---|---|
| 1 | 7 | |
| 350 | 3,317 | |
| - | 0.8% | |
| 4.0 | 2.7 | |
| 8 months ago | 5 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.
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.
Gather-Deployment
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Working with pyflink and parquet
Able to run parquet in pyflink, https://github.com/huseinzol05/Gather-Deployment/tree/master/apache-cluster/5.flink-jupyter
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?
dracula - a brief analysis to the most common words in Dracula, by Bram Stoker
JupyterLab - JupyterLab computational environment.
project - Predict how many points an European football team will end the season with, according to the characteristics of its players. Project for the Big Data Computing course at Sapienza University of Rome (2021-22)
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
TFServing-Demos - TF Serving demos
keytotext - Keywords to Sentences
tf-transformers - State of the art faster Transformer with Tensorflow 2.0 ( NLP, Computer Vision, Audio ).
self-hosted - Sentry, feature-complete and packaged up for low-volume deployments and proofs-of-concept
reddit-streaming - streaming eight subreddits from reddit api using kafka producer & spark structured streaming.
Code-Server - VS Code in the browser
cocalc-docker - DEPRECATED (was -- Docker setup for running CoCalc as downloadable software on your own computer)
pycaret - An open-source, low-code machine learning library in Python