/Kaggle_San_Francisco_Crime_Classification

This project represents:

Primary LanguagePythonMIT LicenseMIT

Kaggle_San_Francisco_Crime_Classification

This project represents:

  1. Solution for Kaggle competition "San Francisco Crime Classification"
  2. Insights for the paper on the ML challenge mentioned above
  3. Web API to use predictive model created for the competition

How to start:

1. Download the repo

  • Create a dictionary for the project on your machine
  • Open terminal in this dictionary and write: git clone https://github.com/Nik-Kras/Kaggle_San_Francisco_Crime_Classification.git

It will download the project and will create a folder for it

2. Create Virtual Environment

  • Open the project folder with VS Code
  • In the VS Code terminal write: conda create --name kaggle_sfcc python=3.8

It will create an environment that will run scripts of the project and where all packages (like pandas) will be installed

3. Start with learning

  • Check the folder called Learning. There you will find simple tasks aimed on training Python skills
  • Make tasks listed in comments, then when all tasks of one script are done - make git commit and push changes
  • To do this follow next commands: git add . git commit -m "YOUR COMMENT ON THIS TASK" git push

4. Continue with src

  • This folder contains actual tasks that shall be done to finish the project (However, I start with simple tasks for training purposes)
  • Check utils.py and make functions as required. They are going to be used for development process

5. Go to notebooks

  • When development stucks and it is difficult to finish some tasks in step #4, go to Jupyter notebooks and try to make a solution there, it could help