course-info.yaml

type: hyperskill
title: NBA Data Preprocessing
language: English
summary: "<p>Data preprocessing is one of the first steps in the machine learning\
  \ workflow. The main idea is to transform raw data into a format that machine learning\
  \ algorithms can easily understand. The predictive performance of a machine learning\
  \ model highly depends on the input data quality. Thus, it's an absolute must to\
  \ know how to improve the quality of your input data by removing the features with\
  \ low predictive value, engineering new ones, and dealing with multicollinearity.\
  \ With this project, you'll apply these concepts to NBA data to get a high-quality\
  \ dataset ready to be fed to a linear model!</p><br/><br/>Learn more at <a href=\"\
  https://hyperskill.org/projects/285?utm_source=ide&utm_medium=ide&utm_campaign=ide&utm_content=project-card\"\
  >https://hyperskill.org/projects/285</a>"
programming_language: Python
content:
- NBA Data Preprocessing
- Topics
mode: Study