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 Interbank
2,358 already enrolled
(44 reviews)
Recommended experience
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
- Matplotlib
- Model Evaluation
- Data Preprocessing
- Pandas (Python Package)
- Machine Learning
- Applied Machine Learning
- Data Visualization Software
- Exploratory Data Analysis
- Predictive Modeling
- Scikit Learn (Machine Learning Library)
- Classification Algorithms
- Data Analysis
- Skills section collapsed. Showing 9 of 12 skills.
Details to know

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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:
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Task #1: Understand the Problem Statement and Business Case
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Task #2: Import Libraries and Datasets
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Task #3: Perform Exploratory Data Analysis
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Task #4: Perform Data Visualization
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Task #5: Prepare the data before Model Training
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Task #6: Understand the Theory and Intuition Behind XG-Boost
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Task #7: Train and Evaluate XG-Boost Algorithm
Recommended experience
Basic python programming and mathematics.
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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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