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p-value.info

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p-value.info | p-value.info Reviews

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Musings on data science, machine learning and stats.

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p-value.info: Advice to graduate students interviewing for industry positions

http://www.p-value.info/2015/03/advice-to-graduate-students.html

Musings on data science, machine learning and stats. Monday, March 9, 2015. Advice to graduate students interviewing for industry positions. A couple of weeks ago I saw a post in a LinkedIn group which went something like this: "I've just received a Ph.D. in physics and I know python and R. I've been applying for data scientist roles. However, I'm not getting much traction. Do you think that I need to learn a BI tool such as Tableau? To summarize, this is a physics Ph.D. OK but what what was your role?

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p-value.info: Howto: build a news aggregator (in 100 LOC)

http://www.p-value.info/2012/12/howto-build-news-aggregator-in-100-loc.html

Musings on data science, machine learning and stats. Monday, December 31, 2012. Howto: build a news aggregator (in 100 LOC). In this post, I'll cover how to build a crude, simple but working news aggregator in about 100 lines of python ( source code. While a complete news aggregator will comprise of at least three steps:. Cluster like documents - - that Techcrunch and GamesIndustry International are both covering the same story. Screen shot below we can see that USA Today, Detroit Free Press, Boston Hera...

3

p-value.info: Data is not the new middle manager

http://www.p-value.info/2015/06/data-is-not-new-middle-manager.html

Musings on data science, machine learning and stats. Friday, June 12, 2015. Data is not the new middle manager. In April, the Wall Street Journal published article that claimed, as its title, " data is the new middle manager. And, further, in the opening paragraph set out this bold claim:. Firms are keeping head counts low, and even eliminating management positions, by replacing them with something you wouldn’t immediately think of as a drop-in substitute for leaders and decision-makers: data. Data tools...

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p-value.info: June 2015

http://www.p-value.info/2015_06_01_archive.html

Musings on data science, machine learning and stats. Friday, June 12, 2015. Data is not the new middle manager. In April, the Wall Street Journal published article that claimed, as its title, " data is the new middle manager. And, further, in the opening paragraph set out this bold claim:. Firms are keeping head counts low, and even eliminating management positions, by replacing them with something you wouldn’t immediately think of as a drop-in substitute for leaders and decision-makers: data. Data tools...

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p-value.info: March 2015

http://www.p-value.info/2015_03_01_archive.html

Musings on data science, machine learning and stats. Saturday, March 21, 2015. The "Creating a Data-Driven Organization" book is now available in Early Release. My book Creating a Data-Driven Organization. Is now available for purchase as part of O'Reilly's early release program. That means you can get access to chapters as they are released before the print date in July 2015. Monday, March 9, 2015. Advice to graduate students interviewing for industry positions. To summarize, this is a physics Ph.D.

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Data Science by Jenda R. Benetka | ZEEF

https://data-science.zeef.com/index

Jenda R. Benetka. Data Analysis, Machine Learning, Python, Visualization, Stats, Tutorials, Blogs, Algorithms, etc. In short, all the fun stuff in one place! Jenda R. Benetka. A Bohemian based in Norway interested in data science, cycling, traveling and photography. Jenda Rybák / rybak.io. Published 1 year ago. Updated 5 months ago. No free hunch - Kaggle Blog. Sebastian Raschka -Data science, ML, . KDnuggets - Latest News. Data Science Weekly Newsletter Archive. Data science @ Right Relevance. Webscope ...

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A Data Analysis of iTunes’ Top Charts Algorithm | dataworks

http://data.betaworks.com/data-analysis-itunes-top-charts-algorithm

A Data Analysis of iTunes’ Top Charts Algorithm. Jan 20, 2015 0 comments. A few days ago I published an in depth analysis of Apple’s iTunes top free chart algorithm, boosting, rank manipulation and algorithmic glitching – on medium.com. Here’s the overview:. Encoded within the iTunes app store algorithm is the power to make or break an app. If you get on its good side, you do really well, and if not, you lose. If these volatile days are deliberate, shouldn’t we be informed? These are people who pour coun...

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Israel, Gaza, War & Data | dataworks

http://data.betaworks.com/israel-gaza-war-data

Israel, Gaza, War & Data. By suman deb roy. Aug 26, 2014 0 comments. Chief scientist at betaworks wrote a recent post. That was featured by NPR, BBC and several other media. Gilad shows that Social Media is being actively used in the art of personalizing propaganda, and while war rages on the ground in Gaza and across Israeli skies, there’s an all-out information war unraveling in social networked spaces. Here are some highlights:. 8230; on social networks:. 8230; on algorithmic filtering:. 8230;and a be...

data.betaworks.com data.betaworks.com

No #MarchMadness Hate on Twitter? | dataworks

http://data.betaworks.com/no-marchmadness-hate-on-twitter

No #MarchMadness Hate on Twitter? Apr 4, 2014 0 comments. Last week the Digg editors came to us with an idea. Wouldn’t it be great if we could do a joint data post on March Madness, but instead of the usual – looking at the account with the most likes, or retweets – we would take a very different approach. Their idea was to find the most disliked team on social media, and map that out. March madness is a love / hate relationship. I hate it right now. Mdash; Dylan Lamb (@dylanlamb ) March 30, 2014. 8220;F...

data.betaworks.com data.betaworks.com

The Digital Flames of Ferguson | dataworks

http://data.betaworks.com/the-digital-flames-of-ferguson

The Digital Flames of Ferguson. By suman deb roy. Aug 26, 2014 0 comments. I wrote a recent post. Articulating the fragmentation around media coverage in Ferguson and the impact of social media in spreading news about events occurring in Ferguson, eventually gaining national attention. Using Twitter trending topics data, I show. How the country’s attention gradually turned to the events transpiring in Ferguson,. The driving factors and what it tells us about. Certain latent kinetics of the Social Web.

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suman deb roy | dataworks

http://data.betaworks.com/author/suman

Retrospective Event Detection in News. By suman deb roy. Aug 25, 2015 0 comments. This is a project developed by Chris Hidey. Who spent this summer interning with us at the betaworks data science team, focusing on natural language understanding and event detection in news streams. In Chris’ words:. The project I worked on this summer was to develop a method that algorithmically generates timelines around a given news subject. A “subject” can be any topic or event, such as. Or the ongoing news coverage of.

data.betaworks.com data.betaworks.com

Digg Reader Visualized: what millions of RSS feeds look like | dataworks

http://data.betaworks.com/digg-reader-visualized-rss-feeds

Digg Reader Visualized: what millions of RSS feeds look like. Jul 1, 2013 0 comments. The mass adoption of RSS as a publishing/subscription protocol, means that it is a great way to bypass the growing number of walled gardens created by social networks, where homophily is dominant. Alternatively, with feed subscription we see much more cross-domain bridging happening. Within the English content region, the popular feeds split into three main types:. Is pretty high up there. 2) To the right, we see a dens...

data.betaworks.com data.betaworks.com

How ‘Instapaper Daily’ remembers the most interesting stories | dataworks

http://data.betaworks.com/how-instapaper-daily-remembers-the-most-interesting-stories

How ‘Instapaper Daily’ remembers the most interesting stories. By suman deb roy. Mar 11, 2014 0 comments. Our attempt to alleviate the first problem was in creating InstaRank. We introduced Instapaper Daily. It culminates into a fascinating dataset for exploring story topics and topic longevity along each timeline. The following analysis uses the last three months of timeline data. However, if the title word space is too sparse, we employ a DBpedia. Whereas ‘The Hunger Games’ will map to topic ‘. 8216;)&...

data.betaworks.com data.betaworks.com

Will your news trend on Facebook? Driving factors behind Facebook trending topics | dataworks

http://data.betaworks.com/will-your-news-trend-on-facebook-driving-factors-behind-facebook-trending-topics

Will your news trend on Facebook? Driving factors behind Facebook trending topics. By suman deb roy. Oct 12, 2014 0 comments. Earlier this year, Facebook announced the launch of trending topics. On its newsfeed page. Like Twitter trends, which reflect the attention landscape in the Twittersphere. Massive pro-democracy protests took place in Hong Kong last week. More than half a million individuals (most of whom were students) decided to occupy Central. The heart of Hong Kong. I chronologically. When enou...

data.betaworks.com data.betaworks.com

media | dataworks

http://data.betaworks.com/category/media

Retrospective Event Detection in News. By suman deb roy. Aug 25, 2015 0 comments. This is a project developed by Chris Hidey. Who spent this summer interning with us at the betaworks data science team, focusing on natural language understanding and event detection in news streams. In Chris’ words:. The project I worked on this summer was to develop a method that algorithmically generates timelines around a given news subject. A “subject” can be any topic or event, such as. Or the ongoing news coverage of.

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Musings on data science, machine learning and stats. Monday, February 8, 2016. The role of model interpretability in data science. This is a cross post of a piece I posted on medium. Feb 1, 2016):. In data science, models can involve abstract features in high dimensional spaces, or they can be more concrete, in lower dimensions, and more readily understood by humans; that is, they are. When, and why, should we favor model interpretability? Interpretable models can be understood by less-technical (non dat...

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