Machine Learning, Propensity Score, & Segmentation Modeling

Predictive Analytics    |    Intermediate
  • 12 Videos | 52m 41s
  • Includes Assessment
  • Earns a Badge
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Both supervised and unsupervised machine learning techniques are at the forefront of the predictive analytics and data mining industry. Discover machine learning features and tools, propensity scoring, and segmentation modeling.

WHAT YOU WILL LEARN

  • identify key features of machine learning
    identify key tools used for machine learning and the high-level process steps
    identify key features of deep learning
    distinguish between supervised and nonsupervised learning methods
    identify key features of ensemble techniques
    measure ensemble error rate
  • recognize key features of the propensity score
    identify key features of propensity score matching
    estimate treatment effects
    apply propensity score matching
    identify key features of segmentation modeling
    distinguish between exploratory data analysis and cluster segmentations

IN THIS COURSE

  • Playable
    1. 
    Machine Learning Overview
    5m 42s
    UP NEXT
  • Playable
    2. 
    Machine Learning Tools and Process
    4m 53s
  • Locked
    3. 
    Deep Learning
    2m 25s
  • Locked
    4. 
    Supervised vs. Unsupervised Methods
    3m 49s
  • Locked
    5. 
    Ensemble Techniques for Machine Learning
    5m 31s
  • Locked
    6. 
    Ensemble Performance Considerations and Metrics
    3m 7s
  • Locked
    7. 
    Propensity Score
    3m 13s
  • Locked
    8. 
    Propensity Score Matching
    4m
  • Locked
    9. 
    Estimating Treatment Effects
    2m 52s
  • Locked
    10. 
    Example of Propensity Score Matching
    2m 36s
  • Locked
    11. 
    Overview of Segmentation Modeling
    3m 15s
  • Locked
    12. 
    EDA and Cluster Segmentation Modeling
    5m 19s

EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE

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