Unsupervised Learning

Machine Learning    |    Beginner
  • 12 Videos | 31m 15s
  • Includes Assessment
  • Earns a Badge
Likes 49 Likes 49
Unsupervised learning can provide powerful insights on data without the need to annotate examples. Explore unsupervised learning, clustering, anomaly detection, and dimensional reduction.

WHAT YOU WILL LEARN

  • describe unsupervised learning and some of the problems it can solve
    describe rule association and how the Apriori algorithm performs tasks
    use the Apriori algorithm for rule association in Python
    describe clustering and the types of problems it applies to
    describe the k-means clustering algorithm
    use scikit-learn to build clusters in Python
  • describe anomaly detection, the types of problems solved with anomaly detection, and some approaches to anomaly detection
    use scikit-learn to perform anomaly detection
    describe the problems with dimensionality and why efforts to reduce dimensionality should be taken
    describe principal component analysis for dimensionality reduction
    use scikit-learn to perform dimensionality reduction
    perform dimensionality reduction and clustering tasks in Python

IN THIS COURSE

  • Playable
    1. 
    What Is Unsupervised Learning?
    2m 22s
    UP NEXT
  • Playable
    2. 
    Rule Association
    1m 44s
  • Locked
    3. 
    A Priori in Python
    3m 22s
  • Locked
    4. 
    Clustering
    1m 39s
  • Locked
    5. 
    K-means Clustering
    1m 48s
  • Locked
    6. 
    Clustering in Python
    1m 38s
  • Locked
    7. 
    Anomaly Detection
    2m 20s
  • Locked
    8. 
    Anomaly Detection in Python
    2m 5s
  • Locked
    9. 
    Dimensionality Reduction
    2m 1s
  • Locked
    10. 
    Principal Component Analysis
    1m 36s
  • Locked
    11. 
    Dimensionality Reduction in Python
    3m 6s
  • Locked
    12. 
    Exercise: Unsupervised Learning in Python
    2m 5s

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