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introduction-to-scientific-machine-learning

https://github.com/smithrwornl/introduction-to-scientific-machine-learning

Science Score: 54.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ✓
    CITATION.cff file
    Found CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ○
    DOI references
  • ○
    Academic publication links
  • ✓
    Committers with academic emails
    1 of 1 committers (100.0%) from academic institutions
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (3.2%) to scientific vocabulary
Last synced: 8 months ago · JSON representation ·

Repository

Basic Info
  • Host: GitHub
  • Owner: SmithRWORNL
  • License: other
  • Language: Jupyter Notebook
  • Default Branch: main
  • Size: 11.5 MB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created almost 2 years ago · Last pushed over 1 year ago
Metadata Files
Readme Contributing License Code of conduct Citation

README.md

Introduction to Scientific Machine Learning

Machine Learning (ML) is a powerful tool for science, but it can be difficult to leverage properly. This tutorial will provide an overview of ML concepts, instruction on how to identify which ML techniques will be useful for given classes of problem, and teach coding skills necessary for working with well known ML libraries.

Viewing the lesson

https://smithrwornl.github.io/Introduction-to-Scientific-Machine-Learning/

Owner

  • Login: SmithRWORNL
  • Kind: user

Citation (CITATION.cff) 

# This template CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to replace its contents
# with information about your lesson.
# Remember to update this file periodically, 
# ensuring that the author list and other fields remain accurate.

cff-version: 1.2.0
title: Introduction to Scientific Machine Learning
message: >-
  Please cite this lesson using the information in this file
  when you refer to it in publications, and/or if you
  re-use, adapt, or expand on the content in your own
  training material.
type: lesson
authors:
  - given-names: Robert
    family-names: Smith
abstract: >-
  An introduction to Python coding for machine learning 
  in scientific fields.
license: CC-BY-4.0

GitHub Events

Total
  • Push event: 11
Last Year
  • Push event: 11

Committers

Last synced: about 1 year ago

All Time
  • Total Commits: 10
  • Total Committers: 1
  • Avg Commits per committer: 10.0
  • Development Distribution Score (DDS): 0.0
Past Year
  • Commits: 10
  • Committers: 1
  • Avg Commits per committer: 10.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Robert Smith s****w@o****v 10
Committer Domains (Top 20 + Academic)
ornl.gov: 1

Issues and Pull Requests

Last synced: about 1 year ago

All Time
  • Total issues: 0
  • Total pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Total issue authors: 0
  • Total pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
Pull Request Authors
Top Labels
Issue Labels
Pull Request Labels

Dependencies

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