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A repository to showcase the upskilling of self in theoretical & applied aspects of data science during the ongoing sabbatical of 23 months(Jan. 2022 - Nov 2023*) along with hand written notes. It's an "attempt" to pursue masters in data science using Internet as an open university.

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Suraj520/data-science

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Data Science

Roadmap

The repository contains hands-on implementation of various key branches of data-science.

Refer the commit history for detailed timeline of commits at link .

Solved numerical problems can be viewed at link

Table of Contents

Section Description
Machine learning Various theoretical concepts covered with hand written notes along with projects.
Zero to One Deep Learning Various deep learning projects
Case Studies Various case studies in the domain of data science which utilise the skills of a data analyst, business analyst and a data scientist
Data Engineering and MLOps Various theoretical concepts covered with hand written notes along with data engineering and mlops projects.
Business intelligence Various business intelligence projects using popular BI tools.
Probability and Statistics Various implementations of concepts used in probability and statistics for data-science and machine learning with hand-written notes.
Linear Algebra Various implementations of concepts used in linear algebra for data-science and machine learning with hand-written notes.

Getting Started

VScode with Anaconda and jupyter notebook integration.

Usage

Most of the files can be easily executed as jupyter notebooks.

Contributing Guidelines

We welcome contributions from anyone and everyone. Please take a moment to review our guidelines before getting started:

Code of Conduct

This project follows a Code of Conduct to ensure that everyone who participates feels safe and respected. Please review it before contributing.

How to Contribute

  1. Fork this repository
  2. Create a branch for your feature or bug fix
  3. Make your changes
  4. Write tests for your changes (if applicable)
  5. Run the tests locally
  6. Submit a pull request

Pull Request Guidelines

  • Make sure that your code adheres to our code style and best practices
  • Include tests that cover your changes (if applicable)
  • Update the README and/or documentation (if applicable)
  • Be descriptive in your pull request description, and reference any relevant issues or pull requests

Issues and Bug Reports

If you encounter any bugs or have feature requests, please file an issue on our issue tracker. When filing a bug report, please include steps to reproduce the issue and any relevant error messages.

Development Setup

If you'd like to contribute but don't know where to start, check out the open issues on our issue tracker or reach out to us on suraj.suraj.4.4.1996@gmail.com. We're happy to help you get set up and find something to work on!

License

By contributing to this project, you agree that your contributions will be licensed under the project's LICENSE.

About

A repository to showcase the upskilling of self in theoretical & applied aspects of data science during the ongoing sabbatical of 23 months(Jan. 2022 - Nov 2023*) along with hand written notes. It's an "attempt" to pursue masters in data science using Internet as an open university.

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