Data Preprocessing

Predictive Analytics    |    Intermediate
  • 7 videos | 25m 15s
  • Includes Assessment
  • Earns a Badge
Rating 4.2 of 68 users Rating 4.2 of 68 users (68)
Predictive analytics delivers the greatest value when the data being modeled is relevant to the business goals. Examine the preprocessing phase of data collection to provide the best predictive model.

WHAT YOU WILL LEARN

  • Recognize what is tidy and what is untidy data
    Identify outliers and determine whether to remove these values
    Perform data transformation, normalization, and scaling
    Recognize important aspects of variable partitioning
  • Recognize important aspects of setting dummy variables and removing variables
    Recognize key approaches for handling missing data
    Use imputation to replace missing data

IN THIS COURSE

  • 4m 32s
    Upon completion of this video, you will be able to recognize what is tidy and what is untidy data. FREE ACCESS
  • 3m 53s
    In this video, you will learn how to identify outliers and determine whether to remove these values. FREE ACCESS
  • Locked
    3.  Transforming, Normalizing, and Scaling Data
    3m 32s
    Find out how to perform data transformation, normalization, and scaling. FREE ACCESS
  • Locked
    4.  Variable Partitioning
    3m 24s
    After completing this video, you will be able to recognize important aspects of partitioning variables. FREE ACCESS
  • Locked
    5.  Dummy Variables and Variable Removal
    3m 10s
    After completing this video, you will be able to recognize important aspects of setting dummy variables and removing variables. FREE ACCESS
  • Locked
    6.  Approaches for Handling Missing Data
    4m 10s
    After completing this video, you will be able to recognize key approaches for handling data that is missing. FREE ACCESS
  • Locked
    7.  Imputation for Continuous Data
    2m 35s
    In this video, you will learn how to use imputation to replace missing data. FREE ACCESS

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