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Added article explaining use of binomial theorem in Combining Predictors lecture.
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pml.md

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- [Comparing Supervised Learning Algorithms](http://www.dataschool.io/comparing-supervised-learning-algorithms/): Comparing 8 common supervised learning algorithms (for regression and classification) on 13 different dimensions.
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## Comprehensive Notes
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## Content Related to the Lectures
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- Complete notes for [Practical Machine Learning](http://sux13.github.io/DataScienceSpCourseNotes/)
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- [Week 4: Combining Predictors -- Math Explained](https://github.com/lgreski/datasciencectacontent/blob/master/markdown/pml-combiningPredictorsBinomial.md)
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## Configuring Github Pages with RStudio for PML Project
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- Step by step instructions to [Configure Github Pages with RStudio](https://github.com/lgreski/datasciencectacontent/blob/master/markdown/pml-ghPagesSetup.md) to support the PML course project.
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## Improving Runtime Performance of Caret
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- Step by step instructions to [implement parallel processing in caret::train()](https://github.com/lgreski/datasciencectacontent/blob/master/markdown/pml-randomForestPerformance.md) on a random forest model, along with runtime performance analysis for a variety of laptops, ranging from an Intel Atom-based tablet to a quad-core i7 processor.
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- Step by step instructions to [implement parallel processing in caret::train()](https://github.com/lgreski/datasciencectacontent/blob/master/markdown/pml-randomForestPerformance.md) on a random forest model, along with runtime performance analysis for a variety of laptops, ranging from an Intel Atom-based tablet to a quad-core i7 processor.
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