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.
Cervical Cancer Risk Prediction Using Machine Learning
Cervical Cancer Risk Prediction Using Machine Learning
Instructor: Ryan Ahmed
Access provided by InZone - Université de Genève
2,245 already enrolled
Learn, practice, and apply job-ready skills with expert guidance
4.7
(44 reviews)
Beginner level
Recommended experience
2 hours
Learn at your own pace
Hands-on learning
What you'll learn
Understand the theory and intuition behind XGBoost Algorithm
Preform exploratory data analysis
Develop, train and evaluate XG-Boost classifier model using Scikit-Learn
Skills you'll practice
Details to know
Shareable certificate
Add to your LinkedIn profile
Taught in English
No downloads or installation required
Only available on desktop
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Learn, practice, and apply job-ready skills in less than 2 hours
- Receive training from industry experts
- Gain hands-on experience solving real-world job tasks
- Build confidence using the latest tools and technologies
About this Guided Project
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:
Task #1: Understand the Problem Statement and Business Case
Task #2: Import Libraries and Datasets
Task #3: Perform Exploratory Data Analysis
Task #4: Perform Data Visualization
Task #5: Prepare the data before Model Training
Task #6: Understand the Theory and Intuition Behind XG-Boost
Task #7: Train and Evaluate XG-Boost Algorithm
Recommended experience
Basic python programming and mathematics.
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Instructor
Offered by
How you'll learn
Skill-based, hands-on learning
Practice new skills by completing job-related tasks.
Expert guidance
Follow along with pre-recorded videos from experts using a unique side-by-side interface.
No downloads or installation required
Access the tools and resources you need in a pre-configured cloud workspace.
Available only on desktop
This Guided Project is designed for laptops or desktop computers with a reliable Internet connection, not mobile devices.
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