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A "production-ready" simple project template to quickly start an Artificial Intelligence (AI), Machine Learning (ML) and/or Data Science (DS) project with basic files, branches and directory structure.

ZenithClown/ai-ml-project-template

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AI-ML Project Template
GitHub issues GitHub forks GitHub stars PRs Welcome

Objective: A simple and well-desgined template structure to start a machine learning/deep learning based projects. The template provides a basic directory structure with additional files (like notebooks/BOILERPLATE.ipynb to perform EDA. In addition, the template is desgined such that code can be deployed into production. Quickly get started working on the code, and prepare documentation as highlighted below. To understand more about the template check HOWTO.md file.


AI-ML 🧠 is an extremely fast growing environment where millions of new commits 👁️ and thousands of users 👨 👩 are actively engaging on a daily basis 📆. To start a new project 📦, one should generally setup a basic project structure with some default branches and files. GitHub Templates solves this by setting up a template from an existing repositories. The template 🧾 provides minimalistic approach to quickly start a machine learning/artificial intelligence project. ⚙️

For more information 💡 on how to use this template and getting started, check HOWTO. Feel free to use the template as it suits you! 🚀 Would be great, if you 🔗 put a link to my template, if you use this repository!

✍️ Project Name

✍️ Please add/modify the project details on your first project start, as documentation is important and let end user have proper knowledge! 🎯 Start by editing all the sections/paragraphs marked with "✍️".

Client Name: ✍️ client name (client details/informations) 🏢

Explorative Results

✍️ The template can also be used in creating research papers 📖, white paper 📝, summary report 📜, production level codes 🏆, etc. Necessary explorative results 🎉 can be documented in this section.

Report Link: ✍️ report link 📕

Modelling Results

✍️ Information about the used models/engines/agents and their performance can be documented here ✨. An AI/ML trained model can be stored in their respective directories.

Report Link: ✍️ report link 📒

Configurations

✍️ A config directory is available to store and configure project with variables, values and/or other informations related to project template.

Project Deployment and Planning

🔖 Relevant information related to project deployment, planning, production ready code. For more information ⁉️ on individual version check CHANGELOG. ✔️

LICENSE & Contributions

🏷️ A CONTRIBUTING.md file, in your open source repository or site, provides potential project contributors with a short guide to how they can help with your project or study group. It is convention to capitalize the word "contributing" as the file title, and to save it as a resource in markdown (hence the extension .md) (source). ✍️ For LICENSE create or add your own file as LICENSE.

Resources

📇 Documentation and/or Resources for your codes, and other mentions can be included in this section! 🔑

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A "production-ready" simple project template to quickly start an Artificial Intelligence (AI), Machine Learning (ML) and/or Data Science (DS) project with basic files, branches and directory structure.

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