In this 1-hour long project-based course, you will learn how to build Classification Trees in Python, using a real world dataset that has missing data and categorical data that must be transformed with One-Hot Encoding. We then use Cost Complexity Pruning and Cross Validation to build a tree that is not overfit to the Training Dataset.
Classification Trees in Python, From Start To Finish
Classification Trees in Python, From Start To Finish
Instructor: Josh Starmer
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4.6
(230 reviews)
Intermediate level
Recommended experience
2 hours
Learn at your own pace
Hands-on learning
What you'll learn
Create Classification Trees in Python
Apply Cost Complexity Pruning in Python
Apply Cross Validation in Python
Create Confusion Matrices in Python
Details to know
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Taught in English
No downloads or installation required
Only available on desktop
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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:
Task 1: Import the modules that will do all the work
Task 2: Import the data
Task 3: Missing Data Part 1: Identifying Missing Data
Task 4: Missing Data Part 2: Dealing With Missing Data
Task 5: Format Data Part 1: Split the Data into Dependent and Independent Variables
Task 6: Format the Data Part 2: One-Hot Encoding
Task 7: Build A Preliminary Classification Tree
Task 8: Cost Complexity Pruning Part 1: Visualize alpha
Task 9: Cost Complexity Pruning Part 2: Cross Validation For Finding the Best Alpha
Task 10: Building, Evaluating, Drawing, and Interpreting the Final Classification Tree
Recommended experience
Familiarity with Python and the theory behind Decision Trees, Cost Complexity Pruning, Cross Validation and Confusion Matrices.
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Instructor
Instructor ratings
4.6 (14 ratings)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
230 reviews
- 5 stars
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- 4 stars
21.30%
- 3 stars
6.08%
- 2 stars
1.30%
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Showing 3 of 230
KD
5
Reviewed on Aug 24, 2020
This is a great course. The instructor does a wonderful job of explaining concepts and providing useful code.
SS
5
Reviewed on Jun 17, 2020
A very informative and well guided short session to understand overview of Classification Trees. Covers lot of important concepts in 1 hour. Highly recommend
YA
5
Reviewed on Sep 13, 2020
Awesome Instructor! Like this course. It clears basic knowledge about DecisionTreeClassifier, Tree Pruning, Dealing with missing Data etc.
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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.