Predicting Salaries with Decision Trees

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

Create a machine learning model using industry standard tools and use it to make salary predictions.

Clock1.5 hours
IntermediateIntermediate
CloudNo download needed
VideoSplit-screen video
Comment DotsEnglish
LaptopDesktop only

In this 1.5 hour long project-based course, you will tackle a real-world prediction problem using machine learning. The dataset we are going to use comes from the U.S. Census Bureau; they recorded a number of attributes such as gender and occupation as well as the salary range for a sample of more than 32,000 Americans. We will fit a decision tree to this data, and try to predict the salary for a person we haven’t seen before. By the end of this project, you will have created a machine learning model using industry standard tools, including Python and sklearn. 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

Python ProgrammingMachine Learningsklearn

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 a dataset from file

  2. Process a dataset so that it can be modelled

  3. Split a dataset into training and testing sets

  4. Fit a decision tree to a dataset and make predictions

  5. Prune a decision tree to improve its accuracy

  6. Generate a graphical representation of a decision tree

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.