machine-learning-neural-python

Introduction to artificial neural nets with Python

https://github.com/carpentries-incubator/machine-learning-neural-python

Science Score: 44.0%

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Keywords

classification deep-learning english explainability image-classification lesson machine machine-learning ml pre-alpha python x-ray
Last synced: 4 months ago · JSON representation ·

Repository

Introduction to artificial neural nets with Python

Basic Info
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  • Stars: 6
  • Watchers: 5
  • Forks: 11
  • Open Issues: 6
  • Releases: 2
Topics
classification deep-learning english explainability image-classification lesson machine machine-learning ml pre-alpha python x-ray
Created about 4 years ago · Last pushed 5 months ago
Metadata Files
Readme Contributing License Code of conduct Citation Authors

README.md

Introduction to artificial neural networks in Python

This half-day lesson gives an introduction to artificial neural networks. During the lesson we prepare and visualise data for algorithm development, and construct a neural network that is able to classify disease in X-rays.

It is the third lesson in the machine learning curriculum. In the final lesson we explore the important area of responsible machine learning.

  1. Introduction to Machine Learning in Python [Lesson materials; Code repository]
  2. Introduction to Tree Models in Python [Lesson materials; Code repository]
  3. Introduction to artificial neural networks in Python [Lesson materials; Code repository]
  4. Responsible machine learning in Python [Lesson materials; Code repository]

Workshop schedule

These lessons are being run at University of Edinburgh as part of the Ed-DaSH Data Science training programme for Health and Biosciences.

The first lessons were taught in May: https://edcarp.github.io/2022-05-24_ed-dash_machine-learning/. For a list of future lessons, see: https://edcarp.github.io/Ed-DaSH/workshops

Contributing

We welcome all contributions to improve the lesson! Maintainers will do their best to help you if you have any questions, concerns, or experience any difficulties along the way.

We'd like to ask you to familiarize yourself with our Contribution Guide and have a look at the more detailed guidelines on proper formatting, ways to render the lesson locally, and even how to write new episodes.

Please see the current list of issues for ideas for contributing to this repository. For making your contribution, we use the GitHub flow, which is nicely explained in the chapter Contributing to a Project in Pro Git by Scott Chacon. Look for the tag good\_first\_issue. This indicates that the maintainers will welcome a pull request fixing this issue.

Maintainer(s)

Current maintainers of this lesson are:

Authors

A list of contributors to the lesson can be found in AUTHORS.

Citation

To cite this lesson, please consult with CITATION.

Owner

  • Name: carpentries-incubator
  • Login: carpentries-incubator
  • Kind: organization

Citation (CITATION)

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
- family-names: "Pollard"
  given-names: "Tom"
  orcid: "https://orcid.org/0000-0002-5676-7898"
- family-names: "Peru"
  given-names: "Giacomo"
  orcid: "https://orcid.org/0000-0001-9770-1978"
- family-names: "van der Burg"
  given-names: "Sven"
  orcid: "https://orcid.org/0000-0003-1250-6968"
- family-names: "Pontes Reis"
  given-names: "Eduardo"
  orcid: "https://orcid.org/0000-0001-5110-457X"
title: "Introduction to artificial neural networks in Python (Carpentries Incubator)"
version: 0.1.0
date-released: 2022-05-24
url: "https://github.com/carpentries-incubator/machine-learning-neural-python"

GitHub Events

Total
  • Create event: 11
  • Release event: 2
  • Issues event: 13
  • Watch event: 1
  • Delete event: 8
  • Issue comment event: 23
  • Push event: 100
  • Pull request review event: 1
  • Pull request event: 13
  • Fork event: 3
Last Year
  • Create event: 11
  • Release event: 2
  • Issues event: 13
  • Watch event: 1
  • Delete event: 8
  • Issue comment event: 23
  • Push event: 100
  • Pull request review event: 1
  • Pull request event: 13
  • Fork event: 3

Issues and Pull Requests

Last synced: 4 months ago

All Time
  • Total issues: 13
  • Total pull requests: 23
  • Average time to close issues: about 1 year
  • Average time to close pull requests: 19 days
  • Total issue authors: 7
  • Total pull request authors: 8
  • Average comments per issue: 1.23
  • Average comments per pull request: 0.52
  • Merged pull requests: 21
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 5
  • Pull requests: 8
  • Average time to close issues: 4 months
  • Average time to close pull requests: 19 days
  • Issue authors: 3
  • Pull request authors: 3
  • Average comments per issue: 2.0
  • Average comments per pull request: 0.5
  • Merged pull requests: 6
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • tompollard (5)
  • alanocallaghan (2)
  • svenvanderburg (2)
  • tiagosousagarcia (1)
  • MelanieIStefan (1)
  • zora-wuw (1)
  • tobyhodges (1)
Pull Request Authors
  • tompollard (13)
  • menomaths (3)
  • hwarden162 (2)
  • GothicArch (2)
  • alanocallaghan (1)
  • svenvanderburg (1)
  • anenadic (1)
  • zkamvar (1)
Top Labels
Issue Labels
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Dependencies

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