This project was completed to practice multiple linear regression model and data visualization. The original data and project was created by Udacity, from the Nanodegree 'Predictive Analytics for Business Nanodegree'. The original project provided the linear regression formula, but for practice purposes, I used python to build the model and calculated my own formula which is similar to the function provided by Udacity.
A jewelry company wants to put in a bid to purchase a large set of diamonds, but is unsure how much it should bid. In this project, I used the data to run multiple linear regression model to get the function to predict the diamond prices, and then created graphs based on the results.
Python
pandas, matplotlib.pyplot, numpy, seaborn, sklearn, statsmodels
diamonds.csv: the historical diamond price data from that company to calculate the linear regression formula.
new-diamonds.csv: the diamonds the company would like to buy and they need to predict the prices of these diamonds.
Predicting Diamond Prices Codes.ipynb: The python code and result of this project
If this project inspired you, gave you ideas to help with your own project, please consider buying me a coffee.