Clustering, Errors, & Validation

Data Science    |    Beginner
  • 10 Videos | 37m 47s
  • Includes Assessment
  • Earns a Badge
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Machine learning is a particular area of data science that uses techniques to create models from data without being explicitly programmed. Examine clustering, errors, and validation in machine learning.

WHAT YOU WILL LEARN

  • describe K-means clustering
    define cluster validation
    define principal component analysis
    describe machine learning errors
    describe underfitting
  • describe overfitting
    apply k-folds cross validation
    describe fall-forward and back-propagation in neural networks
    describe SVMs and their use
    choose the appropriate machine learning method for the given example problems

IN THIS COURSE

  • Playable
    1. 
    K-means Clustering
    4m 42s
    UP NEXT
  • Playable
    2. 
    Using Cluster Validation
    4m 26s
  • Locked
    3. 
    Using Principal Component Analysis
    3m 37s
  • Locked
    4. 
    Introduction to Errors
    4m 4s
  • Locked
    5. 
    Defining Underfitting
    3m 25s
  • Locked
    6. 
    Defining Overfitting
    2m 5s
  • Locked
    7. 
    Using K-folds Cross Validation
    3m 8s
  • Locked
    8. 
    Using Neural Networks
    3m 29s
  • Locked
    9. 
    Support Vector Machines (SVM)
    2m 29s
  • Locked
    10. 
    Exercise: Choose a Machine Learning Method
    1m 51s

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