Data Science Weekly Newsletter

Issue

January 29, 2015

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Editor's Picks

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Providence: Machine Learning At Stack Exchange
At Stack Exchange, we’ve historically been pretty loose with our data analysis. You can see this in the “answered questions” definition (has an accepted answer or an answer with score > 0), “question quality” (measured by ad hoc heuristics based on votes, length, and character classes), “interesting tab” homepage algorithm (backed by a series of experimentally determined weights), and rather naïve question search function. But as our community grows and we tackle more difficult problems we’ve needed to become more sophisticated...

How to Hire Your First Data Scientist
Given the rise in the popularity of Data Science as of late, one only needs to be on recruiter mailing lists, look at company openings, or comb through Linkedin or Indeed's job postings to see that the Data Scientist position comes in a multitude of forms, some true to the name, some simply a Business Analyst in disguise. I remain unconvinced that the majority of employers clearly understand what a Data Scientist is, does, or how they can even help. With that, the purpose of this post is help guide employers and hiring managers looking to add a Data Scientist to their team...

Comments on Warren Sharp's Patriots Fumble Analysis
First, an admission. I am a life-long New England Patriots fan. You could probably assume that because there is no other reason I would put the time into this analysis that I have. On the other hand, I definitely value good statistical analyses leading to well-founded conclusions that elucidate difficult concepts for people instead of adding more confusion...

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Why now is the time to learn R
With such strong demand and such high salaries to offer, it’s no surprise that competition for hiring data scientists is intense. As a result, companies who previously relied on legacy proprietary platforms for statistical analysis are now adopting a new alternative, open source R. So far, it has been chosen by more than two million data scientists and statisticians around the world...

Building A Data Science Portfolio Project Top Down
Having a data science portfolio which showcases your skills in the areas your future employer wants is a great way to get the data science job of your dreams. This article will cover the basics of the top down approach - starting with questions...

Twitter Mapping: Twitter’s Data Editor Highlights Challenges & Possibilities
With more than 500 million tweets sent every day, Twitter data as a whole can seem huge and unimaginable, like cramming the contents of the Library of Congress into your living room. One way of trying to make that big data understandable is by making it smaller and easier to handle by giving it context; by putting it on a map...

Jawbone: Weight Loss - What Really Works
This week, as millions of people try to keep their New Year resolutions past the month of January, we decided to dig into our rich data set to answer a simple question: What are the most effective ways to lose weight?...

A Data-Science Lender Takes on Student Debt
Earnest is one of a new breed of lenders bringing the tools of data science — the modern flood of data and clever software — to consumer finance...

Things in Pandas I Wish I'd Had Known Earlier
This is just a small but growing collection of pandas snippets that I find occasionally and particularly useful -- consider it as my personal notebook...

Computing Recommendations at Extreme Scale with
Apache Flink and Google Compute Engine
Recommender Systems are a very successful application of large scale data processing. They are used to recommend new items of interest to users of a service, such as new movies on Netflix, or shopping articles on Amazon. Recommender systems have become an essential part of most web-based services to enhance the user experience...

Reviewing the American Epilepsy Society Seizure Prediction Challenge
In this blog post, we talk with the top three teams from the American Epilepsy Society Seizure Prediction Challenge...

How racial discrimination in law enforcement actually works
You see it all the time in studies. "We controlled for..." And then the list starts. The longer the better. Income. Age. Race. Religion. Height. Hair color. Sexual preference. Crossfit attendance. Love of parents. Coke or Pepsi. The more things you can control for, the stronger your study is — or, at least, the stronger your study seems...

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Data Scientist - New York Times - NYC
The New York Times is a technology company committed to producing the world's most reliable and highest quality journalism. Our ability to do so relies on a growing, talented team of expert technologists who learn from a tremendous abundance of data unique to this company. As well-documented in the 2014 New York Times Innovation Report, a core function of learning from our data is "the art and science" of understanding and developing our audience, particularly across new digital platforms and products. The Times seeks a Data Scientist to join a growing Data Science Group applying machine learning methods to meet this challenge, in close collaboration with working partners in the newsroom....

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Deep Learning University - Archive Update
It has been a while (November 2014) since our last update to the deeplearning bibliography at deeplearning.university – but underneath is an update with 408 recent papers...

Awesome AI
A curated list of Artificial Intelligence (AI) courses, books, video lectures and papers...

Introduction to Python for Data Mining
Intro to Python and IPython for DataMining ...

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Street-Fighting Mathematics:
The Art of Educated Guessing and Opportunistic Problem Solving
Not a new book, though very well reviewed...
"This book is a treasure trove of intuitive, practical, and brilliant mathematical techniques. Every person with an interest in mathematics, science, or engineering will enjoy this highly stimulating and fun book..."...

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