This repository is made for better understanding of the project 'Machine Learning summer training'. This provides the background information for the project and also critical details of the same.

A dataset was given, named "50 Start-ups". It gave us data of different expenditure of the start ups and their consecutive profits. We were to predict the profit of a start up for a given input parameter.

So our output and target value was profit and we had to choose appropriate input variables. The project is all about applying different ML models and data analysis techniques on this data set.

The repository has a report for the complete tasks done and the report we submitted at the end of this project after completion.

Other files include code files of processing data and predicting using different models. This could be pretty useful if someone needs to see multiple models being used on a dataset. It all gives you an idea of how to write different commands and how to work with code and data. By the way, all code is ready to work, you just need to copy paste it on a python compiler (I recommend Spyder).