README.md

-Prediction-with-Multiple-Regression-

Build a multiple linear regression model by performing EDA and do necessary transformations and select the best model using Python. Dataset Name - 50_startups data. Dataset Name - 50_startups data. Do transformations for getting better predictions of profit and make a table containing R^2 value for each prepared model.

R&D Spend -- Research and devolop spend in the past few years Administration -- spend on administration in the past few years Marketing Spend -- spend on Marketing in the past few years State -- states from which data is collected Profit -- profit of each state in the past few years

1. Follow the Machine Learning Life Cycle Steps.
2. Write proper Insights/Inference on each analysis
3. Do proper EDA on the columns and the data with graphs using seaborn and interpret the graphs.
4. Save the graphs in one folder and zip the folder.
5. Zip the datasets folders for 50_startups data.
6. Write proper print statements while writing the code. Proper rounding of the numbers is also required.
7. Prepare a presentation for both the projects seperately. The presentation should contain -
   1. Objective
   2. Solution
   3. Business Impact