Data Science Weekly - Issue 4
Issue #4 December 19 2013
Editor Picks
Uber's Data Scientist On The Importance Of Knowing One Thing About Everybody Data scientist Bradley Voytek recently spoke about his work at car service Uber. He explained how user information with location and temporal data could be analyzed to find unexpected and useful correlations...
Facebook’s "Deep Learning" Guru Reveals The Future Of AI NYU professor Yann LeCun has spent the last 30 years exploring artificial intelligence, designing “deep learning” computing systems that process information in ways not unlike the human brain. And now he’s bringing this work to Facebook. In this interview he discusses his new project...
Weather Forecasting With Twitter & Pandas Contestants in this Kaggle competition were asked to identify the extent to which Twitter data could be used to forecast the weather. Right off the bat, the challenge reminded me of Google's Flu Trends, a project I find incredibly interesting, so I was fired-up to take a stab at it...
Data Science Articles & Videos
A Neural Network Application: Predicting the Stock Market
Although predicting the stock market is a hot area of research, previous approaches have had their shortcomings. In this project, we aim to improve on other neural network algorithms by adding in data regressions to help us select our input variables. Put simply: we let the data tell us which variables are worth putting in our network...
Programming Smart Molecules: Machine-Learning Algorithms Could Make Chemical Reactions Intelligent
Computer scientists at the Harvard School of Engineering and Applied Sciences (SEAS) and the Wyss Institute for Biologically Inspired Engineering at Harvard University have joined forces to put powerful probabilistic reasoning algorithms in the hands of bioengineers...
Object Recognition: Pete Warden Interview - Co-Founder & CTO Of Jetpac
We recently caught up with Pete Warden, Co-Founder and CTO of Jetpac, which is using Big Data and Object Recognition to build a modern day Yelp...
nEmesis: Which Restaurants Should You Avoid Today?
Computational approaches to health monitoring and epidemiology continue to evolve rapidly. We present an end-to-end system, nEmesis, that automatically identifies restaurants posing public health risks. Leveraging a language noel of Twitter users' online communications, nEmesis finds individuals who are likely suffering from a foodborne illness...
Can Data Turn The Wheel Clean For Pro-Cycling?
Analytics is revolutionizing every sphere of life and competitive sports is no different. Analytics is being used to improve ticket and merchandise sales, draw better labour agreements and player contracts and land lucrative TV and digital media deals. In spite of all such advancements in sports analytics, Professional Cycling seems a few steps behind, given that so much data is available. To end speculation around Tour de France winner Chris Froome, his team released two years Froome’s physical power output data ...
The UN Plot To Force Bayesianism On Unsuspecting Americans
National estimates of the under-5 mortality rate (U5MR) are used to track progress in reducing child mortality. However, for the great majority of developing countries estimating levels and trends in child mortality is challenging, not only because of limited data availability but also because of issues with data quality. We describe a Bayesian penalized B-spline regression model for assessing levels and trends in the U5MR for all countries in the world, whereby biases in data series are estimated through the inclusion of a multilevel model to improve upon the limitations of current methods...
Data Story: John Foreman Of MailChimp On The Data Science Behind Emails
When I was in charge of email at my last startup, the MailChimp blog was a must read. Their approach to email marketing is brilliant so when my colleague suggested I interview MailChimp’s chief data scientist, John Foreman, for a Data Story, I was definitely onboard...
Predicting Highly Cited Scientific Papers
Lots of people make predictions. But very few—especially in the pundit world—are held accountable, or even reexamine their predictions. Recently, Mark Newman, a physicist and network scientist at the University of Michigan, decided to actually check his predictions....
Twitter Sentiment Classification Using Distant Supervision
We introduce a novel approach for automatically classifying the sentiment of Twitter messages. These messages are classified as either positive or negative with respect to a query term. This is useful for consumers who want to research the sentiment of products before purchase, or companies that want to monitor the public sentiment of their brands...
Data Science & Football: Trey Causey Interview - Founder Of The Spread
We recently caught up with Trey Causey - Data Scientist at zulily and Founder of the spread - bringing Data Science and Football together at last...
Jobs
Data Scientist, Machine Zone, Palo Alto CA Develop and investigate hypotheses, structure experiments and build mathematical models to identify game optimization points that will encourage users to play our games more....
Training & Resources
New to Data Science Get started on the path toward becoming a data science practitioner with this helpful list of resources...
Self-Study Guide To Machine Learning There are lots of things you can do to learn about machine learning. There are resources like books and courses you can follow, competitions you can enter and tools you can use. In this post I want to put some structure around these activities and suggest a loose ordering of what to tackle when in your journey from programmer to machine learning master...
DataTau Launches As A Hacker News For Data Scientists First came Hacker News, in 2007. It got developers around the world engaging in conversations about the hottest content on the web, day after day. Yesterday a graduate student at North Carolina State University, Rohit Sivaprasad, started an online community for the subject he’s interested in: data science....
P.S. Are you a Data Scientist? Would you like to share your story/work with the community? If so, we would love to interview you for our blog ... please just email us at team@datascienceweekly.org. Looking forward to hearing from you :)