TypeScript vs. JavaScript: A Guide
September 30, 2024
Article
(17 reviews)
Recommended experience
Beginner level
Basic python programming and mathematics.
(17 reviews)
Recommended experience
Beginner level
Basic python programming and mathematics.
Understand how to leverage the power of machine learning to perform unsupervised segmentation
Learn how to use Plotly to visualize geographical data
Learn how to obtain the optimal number of clusters using the elbow method
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Only available on desktop
In this case study, we will train an unsupervised machine learning algorithm to cluster countries based on features such as economic production, social support, life expectancy, freedom, absence of corruption, and generosity.
The World Happiness Report determines the state of global happiness. The happiness scores and rankings data has been collected by asking individuals to rank their life from 0 (worst possible life) to 10 (best possible life).
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 datasets and libraries
Perform exploratory data analysis
Perform data visualization - part 1
Perform data visualization - part 1
Prepare the data to feed the clustering model
Understand the intuition behind k-means clustering algorithm
Find the optimal number of clusters
Apply k-means using scikit-learn to perform segmentation
Visualize the clusters
Basic python programming and mathematics.
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Practice new skills by completing job-related tasks.
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Available only on desktop
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Reviewed on May 29, 2022
Good project to learn K-Means, good instructor, very comprehensive slides and interesting dataset. Basic Python knowledge needed.
Reviewed on Dec 17, 2022
I learned a lot during this guided project.Thank you very muchAkash Bhat
The University of North Carolina at Chapel Hill
Course
Indian School of Business
Course
Alfaisal University | KLD
Course
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