analisis-numerico-computo-cientifico
ML-Workspace
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analisis-numerico-computo-cientifico | ML-Workspace | |
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1 | 7 | |
44 | 3,317 | |
- | 0.8% | |
0.0 | 2.7 | |
over 1 year ago | 5 months ago | |
Jupyter Notebook | Jupyter Notebook | |
Apache License 2.0 | Apache License 2.0 |
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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.
analisis-numerico-computo-cientifico
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?
osmnx-examples - Gallery of OSMnx tutorials, usage examples, and feature demonstations.
JupyterLab - JupyterLab computational environment.
docker-curriculum - :dolphin: A comprehensive tutorial on getting started with Docker!
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
vqgan-clip-generator - Implements VQGAN+CLIP for image and video generation, and style transfers, based on text and image prompts. Emphasis on ease-of-use, documentation, and smooth video creation.
keytotext - Keywords to Sentences
Kernels - This is a set of simple programs that can be used to explore the features of a parallel platform.
self-hosted - Sentry, feature-complete and packaged up for low-volume deployments and proofs-of-concept
DeepLearning - Contains all my works, references for deep learning
Code-Server - VS Code in the browser
laser - The HPC toolbox: fused matrix multiplication, convolution, data-parallel strided tensor primitives, OpenMP facilities, SIMD, JIT Assembler, CPU detection, state-of-the-art vectorized BLAS for floats and integers
cocalc-docker - DEPRECATED (was -- Docker setup for running CoCalc as downloadable software on your own computer)