Clustering, Errors, & Validation

Data Science    |    Beginner
  • 10 videos | 33m 17s
  • Includes Assessment
  • Earns a Badge
Rating 4.3 of 35 users Rating 4.3 of 35 users (35)
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

  • 4m 42s
    After completing this video, you will be able to describe K-means clustering. FREE ACCESS
  • 4m 26s
    In this video, you will learn how to define cluster validation. FREE ACCESS
  • Locked
    3.  Using Principal Component Analysis
    3m 37s
    In this video, you will learn about principal component analysis. FREE ACCESS
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    4.  Introduction to Errors
    4m 4s
    Upon completion of this video, you will be able to describe machine learning errors. FREE ACCESS
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    5.  Defining Underfitting
    3m 25s
    After completing this video, you will be able to describe what underfitting is. FREE ACCESS
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    6.  Defining Overfitting
    2m 5s
    After completing this video, you will be able to describe what overfitting is. FREE ACCESS
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    7.  Using K-folds Cross Validation
    3m 8s
    In this video, you will learn how to apply k-fold cross validation. FREE ACCESS
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    8.  Using Neural Networks
    3m 29s
    Upon completion of this video, you will be able to describe forward and back propagation in neural networks. FREE ACCESS
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    9.  Support Vector Machines (SVM)
    2m 29s
    Upon completion of this video, you will be able to describe support vector machines and their use. FREE ACCESS
  • Locked
    10.  Exercise: Choose a Machine Learning Method
    1m 51s
    In this video, you will learn how to choose the appropriate machine learning method for given example problems. FREE ACCESS

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