Predict Career Longevity for NBA Rookies using Scikit-learn

Offered By
Coursera Project Network
In this Guided Project, you will:

Visualize data for insights

Create binary classification model using logistic regression

Clock1 hour
BeginnerBeginner
CloudNo download needed
VideoSplit-screen video
Comment DotsEnglish
LaptopDesktop only

By the end of this project, you will be able to apply data analysis to predict career longevity for NBA Rookie using python. Determining whether a player’s career will flourish or not became a science based on the player’s stats. Throughout the project, you will be able to analyze players’ stats and build your own binary classification model using Scikit-learn to predict if the NBA rookie will last for 5 years in the league if provided with some stats such as Games played, assists, steals and turnovers …. etc. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

Skills you will develop

Data SciencePython Programming

Learn step-by-step

In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:

  1. Load the dataset that we will work on

  2. Find insights in our data

  3. Do features selection using correlation heat map

  4. Do binary classification using logistic regression

  5. Adjust the discrimination threshold to increase or decrease the sensitivity to false positives or to other application factors

How Guided Projects work

Your workspace is a cloud desktop right in your browser, no download required

In a split-screen video, your instructor guides you step-by-step

Frequently asked questions

Frequently Asked Questions

More questions? Visit the Learner Help Center.