SAS Institute Of Management Studies - Four Rare Machine Learning Skills All Data Scientists Need
- Offered byCoursera
Four Rare Machine Learning Skills All Data Scientists Need at Coursera Overview
Duration | 6 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Official Website | Explore Free Course  |
Credential | Certificate |
Four Rare Machine Learning Skills All Data Scientists Need at Coursera Highlights
- Earn a Certificate upon completion
Four Rare Machine Learning Skills All Data Scientists Need at Coursera Course details
- 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
Four Rare Machine Learning Skills All Data Scientists Need at Coursera Admission Process
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