Machine Learning Python Challenge: Classification

The aim of this lab is to challenge you on building a supervised machine learning pipeline to predict the probability that a subject will suffer from a heart stroke. Here, you will be tested on data preprocessing, fitting, and evaluation of a classification model.

To get the most from this lab, it is recommended to have confidence and exposure to at least the following libraries: pandas, matplotlib and scikit-learn.

I strongly encourage you to have watched the following courses, available in our content library:

• Building a Machine Learning pipeline with scikit-learn: part 01
• Building a Machine Learning pipeline with scikit-learn: part 02

as well as the following lab:

• Machine Learning Python Challenge: Regression

before starting this challenge.

Updates

January 17th, 2025 - Updated validation function

• Knowledge of classification Completion of the Building a Machine Learning pipeline with scikit-learn: part 02 course is highly recommended

• Machine learning engineers
• Data scientists

• Your ability to create a machine learning pipeline
• Your ability to fit a logistic regression model
• Your ability to evaluate a classification model