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Unsupervised Machine Learning

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Learn to implement and apply unsupervised learning techniques, focusing on clustering and dimension reduction algorithms, in a business environment.

Key AI Functions:Cluster Analysis,Dimensionality Reduction,Unsupervised Learning,Principal Component Analysis (PCA),K Means Clustering

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Description for Unsupervised Machine Learning

Features of Course

Acquire knowledge of unsupervised learning, focusing on clustering and dimension reduction algorithms, and learn to select the appropriate algorithm for your data.

Explain problems suitable for unsupervised learning, describe the curse of dimensionality, and understand its challenges in clustering.

Define and implement common clustering and dimensionality-reduction algorithms, and compare per-cluster model performance.

Gain practical experience with optimal unsupervised learning strategies, comprehend relevant clustering metrics, and apply these techniques in a business environment.

Level: Intermediate

Certification Degree: Yes

Languages the Course is Available: 22

Offered by: On Coursera provided by IBM

Duration: 23 hours (approximately)

Schedule: Flexible

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