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    • NN, Jupiternotebook, geoscience, envronmentalism – IT 2023
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  • coworking Arcturian
    • fotogalerie
    • workshopy
  • novinky
  • prostor coworkistů: uicb, vstecb
    • vstecb_mat_inf_ZS2021
    • vstecb_2022_INF
    • test_LS_2022_Všechny_skupiny
    • NN, Jupiternotebook, geoscience, envronmentalism – IT 2023
  • filmové lokace
  • kontakt&mapa
  • EN
  • captain

NN, Jupiternotebook, geoscience, environmentalism – IT 2022

EPOS – issue tracker: https://epos-ci.brgm.fr/epos-public/issuetracker/-/issues

EPOS: https://intranet.epos-eu.org/user

Issues: epos-public / issuetracker,  GitLab, GitLab Community Edition

EPOS – issue tracker: https://epos-ci.brgm.fr/epos-public/issuetracker/-/issues

EPOS – https://intranet.epos-eu.org/user

Issues: epos-public / issuetracker · GitLab

GitLab Community Edition

JupiterNotebook, at UIb.no et ailleurs

EPOS:

https://epos-no.uib.no:444/#/view/project

https://nnsn.geo.uib.no/nnsn/#/

https://www.kartverket.no/en – observator at Svalbard

https://www.ngu.no/ – karten geologiske kommune

https://www.npolar.no/ –  institut norsk

https://kartkatalog.nve.no/#kart – kart katalog

co a jak instalovat:

https://cocalc.com/features/jupyter-notebookhttps://stackoverflow.com/questions/51706692/load-keras-library-in-jupiter-notebook-using-virtual-environmenthttps://www.geeksforgeeks.org/using-jupyter-notebook-in-virtual-environment/

licence: Norsk: https://data.norge.no/nlod/en/2.0/#_7_disclaimer_of_liability

rozhrani pro prime pouziti jiz nainstalovaneho a pouziti dat z NN:

Enlightenweb

https://www.geeksforgeeks.org/using-jupyter-notebook-in-virtual-environment/

Provenance

https://www.provenance.org/

ENVRI>

https://training.envri.eu/course/index.php

Other tools:

https://www.enlightenweb.com/

EPOS backend:

https://epos-ics-d.brgm-rec.fr/swirrl-api/

Swagger UI

https://iagos-comm.iek.fz-juelich.de/projects/envri-fair

IAGOS Redmine

https://epos-ci.brgm.fr/

Projects · Explore · GitLab

GitLab Community Edition

https://eurocris.org/services/main-features-cerif

Main features of CERIF | euroCRIS

Common European Research Information Format (CERIF) is the comprehensive information model for the domain of scientific research. It is inten…

https://github.com/epos-eu/EPOS-DCAT-AP

GitHub – epos-eu/EPOS-DCAT-AP: DCAT-AP extension for the EPOS solid Earth sciences community

DCAT-AP extension for the EPOS solid Earth sciences community – GitHub – epos-eu/EPOS-DCAT-AP: DCAT-AP extension for the EPOS solid Earth sciences community

https://epos-eu.github.io/SHAPEness-Metadata-Editor/gitpage/index.html

SHAPEness Metadata Editor

https://www.ics-c.epos-eu.org/api/webapi/v1.3/swagger-ui/

EPOS intranet: https://intranet.epos-eu.org/

EPOS – monitoring services: https://data.geus.dk/eposmonitoring/

EPOS – issue tracker: https://epos-ci.brgm.fr/epos-public/issuetracker/-/issues

Issues: epos-public / issuetracker · GitLab

16.9.10:00 https://uib.zoom.us/j/66196910907?pwd=b0dzYXNLcXpvOVdUWVp1NDhqVVZ1Zz0

5/9

20/9

for any queries or questions or for ex-students: feel free to contact me at coworking@arcturian.cz

—norsk

(100) 200 frází – Norština – Čeština – YouTube

3/8/3033

suggestions: Notebook Search (envri.eu)

Notebook Search (envri.eu)


Scaling Machine Learning Infrastructure with Run:AI

When running JupyterHub to serve a large group of data science users, you also need to maintain a machine learning infrastructure, enabling them to run experiments in an efficient and timely manner.

Run:AI automates resource management and orchestration for machine learning infrastructure. With Run:AI, you can automatically run as many compute intensive experiments as needed.

Here are some of the capabilities you gain when using Run:AI:

  • Advanced visibility—create an efficient pipeline of resource sharing by pooling GPU compute resources.
  • No more bottlenecks—you can set up guaranteed quotas of GPU resources, to avoid bottlenecks and optimize billing.
  • A higher level of control—Run:AI enables you to dynamically change resource allocation, ensuring each job gets the resources it needs at any given time.

Run:AI simplifies machine learning infrastructure pipelines, helping data scientists accelerate their productivity and the quality of their models.

JupyterHub: A Practical Guide (run.ai)

Using the JupyterLab Environment | ArcGIS API for Python

Technical:

conda install: How to Setup and Use Your Own Conda Environment in Jupyterhub | Laboratory for Computational Research in Science and Technology (CRSTLab) (umd.edu)

Using the JupyterLab Environment | ArcGIS API for Python

Jupyter Docker Stacks — Docker Stacks documentation (jupyter-docker-stacks.readthedocs.io)

How to make Jupyter Notebook to run on GPU? | TechEntice


installations online: TOP 3:

JupyterLite

Welcome To Colaboratory – Colaboratory (google.com)

CoCalc – Online Jupyter Notebooks

allieurs: Binder (mybinder.org)

Poznámkové bloky v Microsoftu – Visual Studio

free for individuals: Kaggle: Your Machine Learning and Data Science Community

Deepnote – Data science notebook for teams


GitHub – mljar/mercury: Convert Python notebook to web app and share with non-technical users

VM: WebAssembly


personal installation: How to work with Julia on Jupyter Notebook? – GeeksforGeeks


tips for Cloud installation:

Six easy ways to run your Jupyter Notebook in the cloud (dataschool.io)


zásady komunity


swirl API and function index (rdrr.io) swirrl API

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