TensorFlow: K-means Clustering

TensorFlow    |    Intermediate
  • 15 Videos | 1h 5m 34s
  • Includes Assessment
  • Earns a Badge
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Discover how to differentiate between supervised and unsupervised machine learning techniques. The construction of clustering models and their application to classification problems is also covered.

WHAT YOU WILL LEARN

  • distinguish between supervised and unsupervised learning algorithms
    identify the characteristics of supervised learning algorithms
    identify the characteristics of unsupervised learning algorithms
    recognize use cases where unsupervised learning can be applied
    define the objectives of clustering algorithms
    describe the process of k-means clustering to group data
    describe how to implement k-means clustering
  • recall how to install TensorFlow and work with Jupyter notebooks
    generate random data for clustering algorithms
    perform k-means clustering using a TensorFlow estimator
    explore the Iris dataset of flowers
    perform clustering and classification on the Iris dataset
    recall characteristics of unsupervised learning algorithms
    describe the process and use cases of clustering

IN THIS COURSE

  • Playable
    1. 
    Course Overview
    2m 18s
    UP NEXT
  • Playable
    2. 
    Supervised vs. Unsupervised Learning
    4m 37s
  • Locked
    3. 
    Supervised Learning Characteristics
    4m 29s
  • Locked
    4. 
    Unsupervised Learning Characteristics
    3m 5s
  • Locked
    5. 
    Unsupervised Learning Use Cases
    3m 43s
  • Locked
    6. 
    Objectives of Clustering Techniques
    6m 26s
  • Locked
    7. 
    K-means Clustering
    3m 41s
  • Locked
    8. 
    K-means Clustering Algorithm
    3m 20s
  • Locked
    9. 
    Install TensorFlow and Work with Jupyter Notebooks
    2m 21s
  • Locked
    10. 
    Generate Random Data for K-means Clustering
    3m 5s
  • Locked
    11. 
    K-means Clustering Using Estimators
    7m 39s
  • Locked
    12. 
    The Iris Dataset
    3m 44s
  • Locked
    13. 
    Clustering the Iris Dataset
    4m 50s
  • Locked
    14. 
    Exercise: Working with Unsupervised Learning
    2m 50s
  • Locked
    15. 
    Exercise: Working with Clustering
    3m 26s

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