/data-science-for-autos

Python Basics for Data Science Project using automobiles data

Primary LanguageJupyter NotebookMIT LicenseMIT

data-science-for-autos

Python Basics for Data Science Project using automobiles data

In this project the following steps were made:

  • Loaded de CVS file
  • Retreived the data
  • Created the headers on the data
  • Removed the "NaN" datas
  • Applied techniques of Machine Learning, such as:
  • LINEAR REGRESSION
  • MULTIPLE LINEAR REGRESSION
  • REGRESSION PLOT
  • RESIDUAL PLOT
  • DISTRIBUTION PLOT
  • R SQUARED (R^2)

And finally performed the prediction of the car's price for a car with a Highway MPG equals 30

PREDIC_IMG

Used tools

  • IBM Watson Assistant
  • Automobiles data from the UCI Machine Learning Repository

🟦 This project was based on the IBM's Data Analysis course available on edX.org

autos table image using a sample of 5 rows

AUTOS_TABLE