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

• 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

• 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

• 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

• 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

• 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