ML: Diagnose the presence of Breast Cancer with Python

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

Learn how to set up a Jupyter notebook, load data and convert it to data frame.

Preview and visualize loaded data.

Train, test and evaluate a machine learning model.

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

In this 1-hour long project-based course, you will learn how to set up and run your Jupyter Notebook, load, preview and visualize data, then train, test and evaluate a machine learning model that predicts if a patient has breast cancer or not. 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

Machine LearningPython ProgrammingJupyter NotebookData Visualization (DataViz)Supervised Learning

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. By the end of Task 1, you will get an overview of this guided project, Jupyter notebooks which will be used and how you will have set up your notebook environment for this project.

  2. By the end of Task 2, you will have begun the process of building the project template by first loading the data, previewing and exploring it.

  3. By the end of Task 3, you will have checked for missing values, explored data types and visualized features in the data using seaborn.

  4. By the end of Task 4, you will have trained different classifier models, run predictions with them and evaluate their various performances using accuracy score.

  5. By the end of Task 5, you will have combined your predictions with test features and saved your outputs in CSV file format.

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.