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.
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").
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.
✅ Python, R (Python preferred)
✅ Jyputer notebook
✅ Viz - Tableau PowerBI Pandas Seaborn ggplot Bokeh petal Plotly (where-ever applicable)
✅ Html
✅ CSS
✅ Bootstrap
✅ JavaScript
✅ Hosting - GithubPages
Before working on a data science problem, make sure that it has not been completed by some other contributor already.
- 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)
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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.)
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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.
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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. -
Use "camelCase" for the folder you will be creating - example Project "Hand sign detection" in camelCase will be "handSignDetection".
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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. -
PR's will be merged only if the syntax provided above guidelines are ^ followed.
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After you have made the PR, make sure you send the link to PR in slack channel -> #ds-olympus
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Once your PR is merged make sure you are filling up this form for DevIncept's team to track your contributions.
Link
(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.
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Designing a layout
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Further points will be clarified soon.