Data Science

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

Description for Unsupervised Machine Learning

  • 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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