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Data science vs. machine learning: What’s the difference?

IBM Big Data Hub

” “Data science” was first used as an independent discipline in 2001. In 1950, data scientist Alan Turing proposed what we now call the Turing Test , which asked the question, “Can machines think?” Both data science and machine learning are used by data engineers and in almost every industry.

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Themes and Conferences per Pacoid, Episode 8

Domino Data Lab

This month’s article features updates from one of the early data conferences of the year, Strata Data Conference – which was held just last week in San Francisco. In particular, here’s my Strata SF talk “Overview of Data Governance” presented in article form. A very big mess since circa 2001, and now becoming quite a dangerous mess.

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To Balance or Not to Balance?

The Unofficial Google Data Science Blog

A naïve way to solve this problem would be to compare the proportion of buyers between the exposed and unexposed groups, using a simple test for equality of means. Choosing the tuning parameters for data-adaptive methods such as regression trees and MARS is the subject of a large number of research articles and books.

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11 Digital Marketing “Crimes Against Humanity”

Occam's Razor

Making website iterations based on executive opinions, but not site testing. via Jordan Silton] "With testing you can prove if Executives are right or not, and maybe, just maybe figure out WHY. Your website was created in 1996, updated slightly in 2001, and left to rot ever since.

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ML internals: Synthetic Minority Oversampling (SMOTE) Technique

Domino Data Lab

In this article we discuss why fitting models on imbalanced datasets is problematic, and how class imbalance is typically addressed. Their tests are performed using C4.5-generated note that this variant “performs worse than plain under-sampling based on AUC” when tested on the Adult dataset (Dua & Graff, 2017). Chawla et al.,

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Agile Reporting for the Manufacturing Industry: 5 Tips for Success

Jet Global

In 2001, a group of software developers got together at a ski resort in the Wasatch mountains of Utah and drew up a document they called the “Agile Manifesto.” They rejected the classic waterfall model of software development in favor of an iterative approach in which initial prototypes are delivered and tested early in the process.

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Themes and Conferences per Pacoid, Episode 12

Domino Data Lab

Paco Nathan ‘s latest monthly article covers Sci Foo as well as why data science leaders should rethink hiring and training priorities for their data science teams. If you’ve never participated in a Foo event, check out this article by Scott Berkun. Introduction. In mid-July I got to attend Sci Foo , held at Google X.