Predictive Modeling For Temporal Data

  • 10 videos | 44m 5s
  • Includes Assessment
Learn what is the structure of temporal data and how can we clearly define training inputs and outputs for prediction. Also learn how can we utilize feature engineering techniques to extract meaningful insights from temporal data. Finally, find out effective strategies for evaluating model performance and preparing to deploy it in the real world.


  • Understand what predictive models from temporal data are
    Know how to define outcomes to predict
    Know how to find training examples
    Understand how to assemble for feature engineering
    Understand what feature engineering is
  • Know what a feature type is
    Understand the deep feature synthesis algorithm
    Know how stacking relates to deep feature synthesis
    Know how to use previously learned skills to build working model
    Know how to select a correct model


  • 6m 57s
    Learn what predictive models from temporal data are FREE ACCESS
  • 5m 9s
    Learn about defining outcomes to predict. FREE ACCESS
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    3.  Searching For Training Examples
    3m 31s
    Learn about training examples and how to find them FREE ACCESS
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    4.  Assembling Data For Feature Engineering
    4m 29s
    Learn about getting data together for feature engineering FREE ACCESS
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    5.  Feature Engineering- Introduction
    3m 48s
    Find out what feature engineering is FREE ACCESS
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    6.  Feature Types
    5m 1s
    Learn more about the specifics of your data FREE ACCESS
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    7.  Deep Feature Synthesis- Primitives And Algorithm
    5m 4s
    Learn about the Deep Feature Synthesis algorithm FREE ACCESS
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    8.  Deep Feature Synthesis- Stacking
    2m 54s
    Learn why it is called deep feature synthesis FREE ACCESS
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    9.  Modeling and Evaluating
    4m 29s
    Use what you have learned to creat a predictive model FREE ACCESS
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    10.  Model Selection
    2m 44s
    Learn about model validation and selection FREE ACCESS