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Cervical Cancer Risk Prediction Using Machine Learning
  • Level Foundation
  • المدة 3 ساعات hours
  • الطبع بواسطة Coursera Project Network
  • Offered by

عن

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.

الوحدات

Cervical Cancer Risk Prediction Using Machine Learning

    • 1 Readings
    • 1 Plugin
    • 1 Lab
    • 1 Assignment
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1 Assignment

  • Quiz: Assess your knowledge

1 Labs

  • Cervical Cancer Risk Prediction Using Machine Learning

1 Readings

  • Project-based Course Overview

Auto Summary

Discover the power of machine learning in predicting health risks with "Cervical Cancer Risk Prediction Using Machine Learning." This beginner-friendly course, offered by Coursera, is designed to teach you how to build and train an XG-Boost classifier to assess the risk of cervical cancer. You'll work with real-world data from 858 patients, encompassing various features like number of pregnancies, smoking habits, STD history, demographics, and medical records. Over the span of 180 minutes, you'll gain hands-on experience in data science and AI, making this course ideal for those eager to delve into predictive health analytics. Best of all, it's completely free, providing an accessible entry point for anyone interested in using machine learning to make a significant impact in healthcare.

Ryan Ahmed
Instructor

Ryan Ahmed