In this hands-on guided project, we will train unsupervised machine learning algorithms to perform customer market segmentation. Market segmentation is crucial for marketers since it enables them to launch targeted ad marketing campaigns that are tailored to customer's specific needs.
Unsupervised Machine Learning for Customer Market Segmentation
Unsupervised Machine Learning for Customer Market Segmentation
Instructor: Ryan Ahmed
10,979 already enrolled
Guided Project
Learn, practice, and apply job-ready skills with expert guidance
Beginner level
Recommended experience
2 hours (approximately)
Learn at your own pace
No downloads or installation required
Only available on desktop
Hands-on learning
4.7
(322 reviews)
What you'll learn
Understand how to leverage the power of machine learning to transform marketing departments and perform customer segmentation
Compile and fit unsupervised machine learning models such as PCA and K-Means to training data.
Understand the theory and intuition behind Principal Component Analysis (PCA) and k-means clustering machine learning algorithm
Learn how to obtain the optimal number of clusters using the elbow method
Skills you'll practice
- Category: Artificial Intelligence (AI)
- Category: Machine Learning
- Category: clustering
- Category: Python Programming
- Category: unsupervised machine learning
Details to know
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Guided Project
Learn, practice, and apply job-ready skills with expert guidance
Beginner level
Recommended experience
2 hours (approximately)
Learn at your own pace
No downloads or installation required
Only available on desktop
Hands-on learning
4.7
(322 reviews)
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
Visualize and explore datasets
Understand the theory and intuition behind k-means clustering machine learning algorithm
Learn how to obtain the optimal number of clusters using the elbow method
Use Scikit-Learn library to find the optimal number of clusters using elbow method
Apply k-means using Scikit-Learn to perform customer segmentation
Apply Principal Component Analysis (PCA) technique to perform dimensionality reduction and data visualization
Recommended experience
Basic python programming and mathematics.
1 project image
Instructor
Instructor ratings
4.8 (11 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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At the top of the page, you can press on the experience level for this Guided Project to view any knowledge prerequisites. For every level of Guided Project, your instructor will walk you through step-by-step.
Yes, everything you need to complete your Guided Project will be available in a cloud desktop that is available in your browser.
You'll learn by doing through completing tasks in a split-screen environment directly in your browser. On the left side of the screen, you'll complete the task in your workspace. On the right side of the screen, you'll watch an instructor walk you through the project, step-by-step.
