CourseTechnology
Cervical Cancer Risk Prediction Using Machine Learning
By External Provider
About this course
In this hands-on project, we will build and train an XG-Boost classifier to predict whether a person has a risk of having cervical cancer. Cervical cancer kills about 4,000 women in the U.S. and about 300,000 women worldwide. Data has been obtained from 858 patients and include features such as number of pregnancies, smoking habits, Sexually Transmitted Disease (STD), demographics, and historic medical records.
What you will learn
- Understand the theory and intuition behind XGBoost Algorithm
- Preform exploratory data analysis
- Develop, train and evaluate XG-Boost classifier model using Scikit-Learn