Posts Tagged ‘ Big Data ’

Reading Everything is Obvious by Duncan Watts

February 15, 2017
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Reading Everything is Obvious by Duncan Watts

In his book, Everything is Obvious (Once You Know the Answer): Why Common Sense Fails, Duncan Watts, a professor of sociology at Columbia, imparts urgent lessons that are as relevant to his students as to self-proclaimed data scientists. It takes only nominal effort to generate narrative structures that retrace the past, Watts contends, but developing lasting theory that produces valid predictions requires much more effort than common sense. Watts’s is…

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Data for the People

February 5, 2017
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Data for the People, by Andreas Weigend, is coming out this week, or maybe it came out last week. Andreas is a leading technologist (at least that's the most accurate one-word description I can think of), and I have valued his insights ever since we we...

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Deep thinking about your data

February 3, 2017
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Deep thinking about your data

In the on-going series of posts about the IMDB dataset, from Kaggle, I have so far looked at several of the scraped variables, including the number of faces on movie posters (1, 2), plot keywords (3), and movie rating by title year (4). In this post, I tackle the variables resulting from a data merge between IMDB and Facebook. These columns have names like "Director Facebook Likes", "Actor 1 Facebook…

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Apparently Hollywood does not recycle action-movie plots. The data said so, so it must be right

January 25, 2017
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Apparently Hollywood does not recycle action-movie plots. The data said so, so it must be right

Today I continue to explore the movie dataset, found on Kaggle. To catch up with previous work, see the blog posts 1 and 2. One of the students came up with an interesting problem. Among the genre of action movies, are there particular plot elements that are correlated with box office? This problem is solvable because the dataset contains a variable called "plot keywords" lifted from IMDB. Plot keywords are…

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Counting is hard, especially when you don’t have theories

January 19, 2017
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Counting is hard, especially when you don’t have theories

Exploring the data about movies, uncovering data issues

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Good models + Bad data = Bad analysis

January 18, 2017
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Good models + Bad data = Bad analysis

Example showing how to diagnose bad data in data science models

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Royal Economic Society Webcasts on Econometrics

January 17, 2017
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Royal Economic Society Webcasts on Econometrics

The Royal Economic Society has recently released videos of interviews with three leading econometricans, recorded during the Society's 2016 Meeting. These are: Econometric Methods: An interview with Bruce HansenAn interview with Andrew ChesherUsin...

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Why do Decision Trees Work?

January 6, 2017
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Why do Decision Trees Work?

In this article we will discuss the machine learning method called “decision trees”, moving quickly over the usual “how decision trees work” and spending time on “why decision trees work.” We will write from a computational learning theory perspective, and hope this helps make both decision trees and computational learning theory more comprehensible. The goal … Continue reading Why do Decision Trees Work?

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ASA President meets OCCAM data

December 27, 2016
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Just leaving this quote from ASA President Jessica Utts here (Source: Amstat News Dec 2016): A few days ago, I was in Vietnam and took a four-hour bus ride from Ha Long Bay to Hanoi. When I arrived, my fitness tracker had given me credit for taking 9,124 steps and climbing 81 flights of stairs during those four hours, even though I only left my seat once during a short…

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What do these items have in common?

December 19, 2016
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What do these items have in common?

What do the following items have in common? A. Motion-detection light switch in your office that shuts off while you're typing at your computer B. Automatic flush that turns on while you're seated C. Voice-recognition system that picks up ambient noise and asks you to repeat something you didn't say D. Auto-correct software that flips a correct spelling to the wrong one you didn't anti-auto-correct the last time E. Fuzzy-logic…

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