https://github.com/datarootsio/ml-skeleton-py

A best-practices first project template that allows you to get started on a new machine learning project.
https://github.com/datarootsio/ml-skeleton-py

ai best-practices docker docker-compose machine-learning machine-learning-template python shim template unittesting

Last synced: about 11 hours ago
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A best-practices first project template that allows you to get started on a new machine learning project.

• Host: GitHub
• URL: https://github.com/datarootsio/ml-skeleton-py
• Owner: datarootsio
• License: mit
• Created: 2020-08-10T14:07:00.000Z (over 4 years ago)
• Default Branch: master
• Last Pushed: 2021-08-26T14:06:47.000Z (about 3 years ago)
• Last Synced: 2023-11-07T17:23:50.173Z (about 1 year ago)
• Topics: ai, best-practices, docker, docker-compose, machine-learning, machine-learning-template, python, shim, template, unittesting
• Language: Python
• Homepage:
• Size: 35.3 MB
• Stars: 134
• Watchers: 12
• Forks: 17
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        

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**NOTE:** This is a best-practices first project template that allows you to get started on a new machine learning project. For more info on how to use it check out [HOWTO.md](HOWTO.md). Feel free to use it how it suits you best 🚀

# `PROJECT NAME`

> project for: `client name`  

## Objective

`ADD OBJECTIVE OF CASE`

## Explorative results

`SHORT SUMMARY AND LINK TO REPORT`

## Modelling results

`SHORT SUMMARY AND LINK TO REPORT`

## Usage

`ADD EXPLANATION`

## Configuration

`RELEVANT INFO ON CONFIGURATION`

## Deploy

`RELEVANT INFO ON DEPLOYMENT`

> copyright by `your company`

> main developer `developer_name` (`developer email`)