Git Product home page Git Product logo

ds-olympus-'s Introduction

DS-Olympus ⚡️

This repo will serve as the main repository for project "DS Olympus" -


image

A collection of various data science problems along with it's dataset and solutions in various fields like machine learning, deep learning (image recognition, natural language processing) all at one place.



⚠️ Before Strarting

This project is an open-source project at it's early stages, ideas, thoughts, clarification or anything at all, are welcome!

You can directly ping me on Twitter or Slack (searching "Utkarsh Program Admin").

🚩 What Problem are we looking to solve?

Recently, many students have leaned towards learning Data Science and look forward to specializing in the field. Now, we do know that there are many great github repos out there that have collection of various resources, but then it's still a huge task to refer those for beginners. DS Olympus aims at solving those problems by creating a collection of various problems in Data Science, featuring -

✅ The problem we are looking to solve based on the data

✅ Link to dataset.

✅ Most accurate solution to that problem in Jyputer notebook.



🚩 Tech Stack

⚡️ For DataScience

✅ Python, R (Python preferred)
✅ Jyputer notebook
✅ Viz - Tableau PowerBI Pandas Seaborn ggplot Bokeh petal Plotly (where-ever applicable)

⚡️ For Web Dev

✅ Html
✅ CSS
✅ Bootstrap
✅ JavaScript
✅ Hosting - GithubPages



🚩 Contribution Guide


Before making any issues, make sure to check the ones already closed.

Before working on a data science problem, make sure that it has not been completed by some other contributor already.



General

  • Never. Repeat. Never make a pull request directly to the main branch.
  • Fork the repository, and make sure you make pull requests to the branch created by you. (Again, never to the main branch)
  • Make sure you dm if you have any doubts whatsoever. (Slack channel #ds-olympus)

For DataScience

  1. Make an Issue for each problem you are looking to solve. (For example, if you have 2 projects in mind, one from machine learning and deep learning, make sure you make different issues for each.)

  2. If you have multiple problems in mind-make sure you are raising multiple issues for each, i.e for each issue should be related to one single data science problem, raise multiple issues for multiple problems.

  3. Find great problems related in various fields
    ✅ Machine Learning
    Machine learning projects will be under "machineLearning" folder.
    ✅ Deep Learning (Image Recognition, Natural Language Processing, etc)
    Deep learning projects will be under "deepLearning" folder.

  4. Use "camelCase" for the folder you will be creating - example Project "Hand sign detection" in camelCase will be "handSignDetection".

  5. The folder should contain -
    ✅ Jyputer Notebook (complete explanation and code to the problem)
    If you are working on opencv projects and aren't using jyputer notebook, make sure you include your code in .py format or R format
    ✅ Dataset (if it it less than 100MB), Also if you have problems uploading the file or bandwidth issue, make sure you make a section about dataset in Jyputer notebook
    ✅ ReadMe - A little intro about your problem and the tech stack used along with the IDE's.

  6. PR's will be merged only if the syntax provided above guidelines are ^ followed.

  7. After you have made the PR, make sure you send the link to PR in slack channel -> #ds-olympus

  8. Once your PR is merged make sure you are filling up this form for DevIncept's team to track your contributions.
    Link


For WebDev

(This is required at a later stage of the project and can easily be done by a single contributor too).

Web dev part is a work in progress, **before making issues and pr's make sure you dm on Slack channel #ds-olympus or (Utkarsh PA) OR Twitter, pitching ideas that you think can make the site look aesthetic and minimalistic.

  1. Designing a layout

  2. Further points will be clarified soon.

OUR VALUABLE CONTRIBUTORS✨

ds-olympus-'s People

Contributors

dethebera avatar sitanshu-ai avatar kanakmi avatar rahulraj31 avatar manasi2001 avatar payaldutta avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.