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SAS Institute Of Management Studies - Four Rare Machine Learning Skills All Data Scientists Need 

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  • Public/Government Institute

Four Rare Machine Learning Skills All Data Scientists Need
 at 
Coursera 
Overview

Duration

6 hours

Total fee

Free

Mode of learning

Online

Official Website

Explore Free Course External Link Icon

Credential

Certificate

Four Rare Machine Learning Skills All Data Scientists Need
Table of content
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  • Overview
  • Highlights
  • Course Details
  • Curriculum

Four Rare Machine Learning Skills All Data Scientists Need
 at 
Coursera 
Highlights

  • Earn a Certificate upon completion
Details Icon

Four Rare Machine Learning Skills All Data Scientists Need
 at 
Coursera 
Course details

More about this course
  • This course covers the most neglected yet critical skills in machine learning, four vital techniques that are very rarely covered - most courses and books omit them entirely

Four Rare Machine Learning Skills All Data Scientists Need
 at 
Coursera 
Curriculum

Four Rare Machine Learning Skills All Data Scientists Need

Course overview

Uplift modeling I: optimize for influence and persuade by the numbers

Uplift modeling II: modeling over treatment and control groups

Uplift modeling III: how it works ? for banks and for Obama

Uplift modeling IV: improving churn modeling, plus other applications

Accuracy fallacy: orchestrating the media's bogus coverage of ML

More accuracy fallacies: predicting psychosis, criminality, & bestsellers

P-hacking: a treacherous pitfall

P-hacking: your predictive insights may be bogus

P-hacking: how to ensure sound discoveries

Ensemble models and the Netflix Prize

Supercharging prediction: ensembles & the generalization paradox

DEMO - Training an ensemble model (optional)

Course conclusions

The Machine Learning Glossary (optional)

Complementary readings on uplift modeling (optional)

Complementary reading related to the accuracy fallacy (optional)

Complementary materials on p-hacking (optional)

The generalization paradox of ensembles (optional)

Further learning options

Uplift modeling I: optimize for influence and persuade by the numbers

Uplift modeling II: modeling over treatment and control groups

Uplift modeling III: how it works ? for banks and for Obama

Uplift modeling IV: improving churn modeling, plus other applications

Accuracy fallacy: orchestrating the media's bogus coverage of ML

More accuracy fallacies: predicting psychosis, criminality, & bestsellers

P-hacking: a treacherous pitfall

P-hacking: your predictive insights may be bogus

P-hacking: how to ensure sound discoveries

Ensemble models and the Netflix Prize

Supercharging prediction: ensembles & the generalization paradox

Graded course completion quiz

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Four Rare Machine Learning Skills All Data Scientists Need
 at 
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