The objective of this project is to predict whether a patient has kyphosis or not, based on given features and diagnostic measurements such as age and number of vertebrae. Kyphosis is an abnormally excessive convex curvature of the spine. This guided project is practical and directly applicable to the healthcare industry. You can add this project to your portfolio of projects which is essential for your next job interview.
Machine Learning for Kyphosis Disease Classification
Learn, practice, and apply job-ready skills with expert guidance
4.6
(13 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 decision trees and random forest classifier models
Build, train and test a decision tree and random forest classifier models in Sklearn
Perform data cleaning, feature engineering and visualization
Skills you'll practice
- Data Processing
- Scikit Learn (Machine Learning Library)
- Predictive Modeling
- Data Science
- Decision Tree Learning
- Feature Engineering
- Data Visualization Software
- Python Programming
- Data Cleansing
- Predictive Analytics
- Data Manipulation
- Applied Machine Learning
- Data Transformation
- Classification And Regression Tree (CART)
- Machine Learning
- Random Forest Algorithm
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:
Understand the Problem Statement and Business Case
Import Libraries and Datasets
Practice Opportunity #1 [Optional]
Perform Data Visualization
Practice Opportunity #2 [Optional]
Create Training and Testing Datasets
Train a Logistic Regression Classifier Model
Evaluate Trained Model Performance
Understand the theory of Decision Trees and Random Forest
Improve the Model
Practice Opportunity #3 [Optional]
Recommended experience
python programming and basic math background
11 project images
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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Learner reviews
4.6
13 reviews
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Showing 3 of 13
RA
4
Reviewed on Oct 7, 2022
Many codes were already written. I preferred to see the instructor's keystrokes and type the codes myself.
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Frequently asked questions
By purchasing a Guided Project, you'll get everything you need to complete the Guided Project including access to a cloud desktop workspace through your web browser that contains the files and software you need to get started, plus step-by-step video instruction from a subject matter expert.
Because your workspace contains a cloud desktop that is sized for a laptop or desktop computer, Guided Projects are not available on your mobile device.
Guided Project instructors are subject matter experts who have experience in the skill, tool or domain of their project and are passionate about sharing their knowledge to impact millions of learners around the world.