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Data Science Blog

Machine learning & data science for beginners and experts alike.
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Community Content Engineer
Community Content Engineer
Alteryx
Alteryx

Have you struggled to deploy your predictive models in a timely manner before they become obsolete? This article will show you how Alteryx Promote solves this challenge by deploying your model into a RESTful API that can be called from a wide variety of enterprise applications.

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Community Content Engineer
Community Content Engineer
Community Content Engineer
Community Content Engineer

BIAS VS VARIANCE.png

There are two types of model errors when making an estimate; bias and variance. Understanding both of these types of errors, as well as how they relate to one another is fundamentally important to understanding model overfitting, underfitting, and complexity.

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Community Content Engineer
Community Content Engineer

ALL MODELS ARE WRONG.png

“Essentially, all models are wrong, but some models are useful.” Unpacking the famous George Box quote.

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Community Content Engineer
Community Content Engineer

 

SPECIFICATION GAMING1.png

Machines are not constrained by human experience or expectations, only by what we give them as inputs. This can be exciting and beautiful, or dangerous.

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Alteryx
Alteryx

MULTICOLLINEARITY.png

Dr. Dan imparts some intuition behind the problems associated with predictor collinearity (also known as multicollinearity), and provides some rules of thumb about when, and when not, to be concerned.

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Alteryx Alumni (Retired)

Most real-world data-science design patterns combine several models to solve a single business problem.  This post surveys the most common and effective techniques for combining models.  Once you make it through this post (and its predecessors), you'll be ready to take on the design patterns we'll begin learning in 2017. 

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Alteryx Alumni (Retired)

Cross validation (CV) is a difficult topic.  There are many ways to do CV, and articles on the subject can be very technical.  This blog post is a gentle introduction to CV.  Read it and you'll find it much easier to understand later posts describing data-science design patterns that use CV. 

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Alteryx Alumni (Retired)

An advanced-analytics model's induction algorithm is its prediction engine.  Learn what induction-algorithm features distinguish parametric statistical models and machine-learning models.

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Alteryx Alumni (Retired)

Citizen data scientist?  Learn design patterns that let you use Alteryx to build data-science expertise into your data analyses and analytical models!

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Alteryx Alumni (Retired)

Have you mastered the concepts discussed in Demystifying the R-based Tools, Part 1? Are you ready to take the next step on your Predictive Analytics journey? If so, this post is for you!

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Alteryx Alumni (Retired)

 

bloated-gopher.jpgR can be a bit bloated someitmes. Learn how to make your R models more effecient.

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