Predict basketball player efficiency ratings by using machine learning and Visual Studio Code

Module
12 Units

Beginner

Data Scientist

Student

Visual Studio Code

By using anonymized data from real and animated basketball players in the upcoming film Space Jam: A New Legacy, create a machine learning model to cleanse data to be used during games. Also explore bimodal data distributions by using Python in Visual Studio Code.

Learning objectives

In this module, you will:

Use Python, pandas, and Visual Studio Code.
Cleanse and manipulate data that requires critical analysis.
Use machine learning to cleanse and complete data.
Prepare data to be used for multiple customer-facing purposes.

Tip

This module is part of a multimodal learning experience. Start the module to see how you can follow along!

Prerequisites

Visual Studio Code, with the Python extension installed

Introduction min
Exercise - Set up your local environment for data science coding min
Exercise - Data cleansing part 1 - Find missing values min
Exercise - Data cleansing part 2 - Drop columns and rows min
Exercise - Data exploration part 1 - Check for outliers min
Exercise - Data exploration part 2 - Check the distribution of the data min
Exercise - Data exploration part 3 - Discover data that represents more than one population min
Exercise - Data manipulation part 1 - Add qualifying player information min
Exercise - Data manipulation part 2 - Impute missing values for columns min
Exercise - Data manipulation part 3 - Impute missing values by using machine learning min
Knowledge check min
Summary min