coding-for-ml

Learning materials for Coding for Machine Learning and Data Science

https://github.com/health-data-science-or/coding-for-ml

Science Score: 67.0%

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
    Found 6 DOI reference(s) in README
  • Academic publication links
    Links to: zenodo.org
  • Academic email domains
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (8.2%) to scientific vocabulary
Last synced: 10 months ago · JSON representation ·

Repository

Learning materials for Coding for Machine Learning and Data Science

Basic Info
Statistics
  • Stars: 19
  • Watchers: 1
  • Forks: 4
  • Open Issues: 4
  • Releases: 4
Created over 5 years ago · Last pushed 10 months ago
Metadata Files
Readme Changelog License Citation

README.md

DOI

Binder

Python for health data science: a hands-on introduction

Learning materials for Coding for Machine Learning and Data Science

This material is also available as a Jupyter Book

Installing the virtual environment

Details of a conda virtual environment is available in binder/environment.yml

  1. Clone the repo
  2. Navigate to the repo in a terminal (Mac/Linux) or anaconda prompt (Windows)
  3. Create the virtual environment
  4. conda env create -f binder/environment.yml

  5. Activate the environment

  6. conda activate hds_code

  7. Launch Jupyter-lab to edit and run code

  8. jupyter-lab

Citation

Please cite using the zenodo link. LaTex is:

@software{monks_thomas_2023_8377497, author = {Monks, Thomas}, title = {{Python for health data science: a hands-on introduction}}, month = sep, year = 2023, note = {{If you use this software, please cite it using the metadata from this file.}}, publisher = {Zenodo}, version = {v2.0.1}, doi = {10.5281/zenodo.8377497}, url = {https://doi.org/10.5281/zenodo.8377497} }

Owner

  • Name: Health Data Science and Operations Research
  • Login: health-data-science-OR
  • Kind: organization

Citation (CITATION.cff)

# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!

cff-version: 1.2.0
title: 'Python for health data science: a hands-on introduction'
message: >-
  If you use this software, please cite it using the
  metadata from this file.
type: software
authors:
  - given-names: Thomas
    family-names: Monks
    affiliation: 'University of Exeter '
    orcid: 'https://orcid.org/0000-0003-2631-4481'
identifiers:
  - type: doi
    value: 10.5281/zenodo.7107920
    description: v2.0.0
repository-code: 'https://github.com/health-data-science-OR/coding-for-ml'
url: 'https://www.pythonhealthdatascience.com'
keywords:
  - Python
  - Health
  - Data Science
license: MIT
version: 2.0.0

GitHub Events

Total
  • Watch event: 2
  • Issue comment event: 1
  • Push event: 2
Last Year
  • Watch event: 2
  • Issue comment event: 1
  • Push event: 2

Dependencies

Dockerfile docker
  • ubuntu 20.04 build
binder/environment.yml pypi
  • py7zr ==0.20.0
  • rich ==12.5.1
  • scikit-learn ==1.1.2
content/03_mgt/03_pypi/environment.yml pypi
  • pytest-cov ==2.10.0
  • setuptools >=51.1.2
  • twine >=3.3.0
  • wheel >0.36.2
content/03_mgt/03_pypi/requirements.txt pypi
  • matplotlib >=3.1.3
  • numpy >=1.18.1
  • pandas >=1.0.1
  • scipy >=1.4.1
  • seaborn >=0.10.0
content/03_mgt/03_pypi/setup.py pypi