fake-news
ML-Workspace
| fake-news | ML-Workspace | |
|---|---|---|
| 1 | 7 | |
| 130 | 3,324 | |
| - | 0.4% | |
| 4.1 | 2.7 | |
| over 3 years ago | 6 months ago | |
| Jupyter Notebook | Jupyter Notebook | |
| GNU Affero General Public License v3.0 | 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.
fake-news
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Building an End-to-End Machine Learning Application From Idea to Deployment
Hi I had the same issue I think code for EDA part is in https://github.com/mihail911/fake-news/blob/master/notebooks/data_analysis.ipynb
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?
onepanel - The open source, end-to-end computer vision platform. Label, build, train, tune, deploy and automate in a unified platform that runs on any cloud and on-premises.
JupyterLab - JupyterLab computational environment.
mt5-M2M-comparison - Comparing M2M and mT5 on a rare language pairs, blog post: https://medium.com/@abdessalemboukil/comparing-facebooks-m2m-to-mt5-in-low-resources-translation-english-yoruba-ef56624d2b75
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
fastMONAI - Simplifying deep learning for medical imaging
keytotext - Keywords to Sentences
mlf-core - CPU and GPU deterministic and therefore fully reproducible machine learning pipelines using MLflow.
self-hosted - Sentry, feature-complete and packaged up for low-volume deployments and proofs-of-concept
bert-sklearn - a sklearn wrapper for Google's BERT model
Code-Server - VS Code in the browser
peacasso - UI interface for experimenting with multimodal (text, image) models (stable diffusion).
cocalc-docker - DEPRECATED (was -- Docker setup for running CoCalc as downloadable software on your own computer)