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CleverInsight Open AI Foundation

Sparx Contributors Challenges

Sparx is a data preprocessing library which has been created to make feature engineering simplified. To be a part of the active contributor for sparx library, its mandatory to complete this challenge which helps you to understand the data wrangling and python optimization.

Dear AI Foundation Aspirants,

We hope everyone have gone throught the resource material's provided during vacations. Now in-order to contribute and become a volunteer of CleverInsight OpenAI Foundation, we have a challenge which resembles like the one you are going to face in upcoming days. So you are request to follow the guidelines.

  • Challenge start at today and end by 12th Jan 2020 night at 11pm.
  • Kindly follow the instructions.

How to contribute to this challenge. Kindly follow the video below.

Prerequisite

  • As python version 2 has been retired this year, we recommend you to install Ananconda version 3.7 | install.
  • Git version control | install.
  • Any recommended code-editor Sublime Text, VSCode, PyCharm.
  • Better understanding of pandas,numpy python packages.
  • Create an account in Github.com and get your username.

How to contribute.

  1. Visit after login into Github https://github.com/cleverinsight-open-ai-foundation/challenges
  2. Fork this challenges repository now you get exact copy cloned into your account.
  3. On your cloned repository you can see clone or download green button. Click that button now copy your git repository url.
  4. From you local machine open terminal if MacOs or Right click > Git bash here on windows machine.
  5. Run the command git clone url url is the one you copied in step 3. For ex: git clone https://github.com/cleverinsight-open-ai-foundation/challenges.git and Press Enter.
  6. Now if you type ls on Mac or dir in Windows you can see challenges folder.

Directory structure

challenges
│   README.md
│  .gitignore
│   data.csv
│   init.py
│   LICENSE
│   VERSION

Problem Statement

init.py contains all codes for this challenges. There is a class called Load inside the init.py with lots of incomplete methods leftover intentionally. Now you can select any one incomplete method and solve using the Docstring given on the method definition.

  • Once you write method which is incomplete.
  • Test the method with different edge cases using pytest
  • Run pylint init.py and make sure the code is PEP8 standard with 10/10 score.
  • Git commit with correct message
  • Now push the core into your repository using the command git push origin master.
  • Now send a Pull Request (PR) from your repo to the original source repo.

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