Data Science Weekly Newsletter - Issue 8

Issue #8

January 16 2014

Editor Picks

 
  • US Military Scientists Solve The Fundamental Problem Of Viral Marketing

    Network theorists working for the US military have worked out how to identify the small “seed” group of people who can spread a message across an entire network. Their method is relatively straightforward. It is based on the idea that an individual will eventually receive a message if a certain proportion of his or her friends already have that message. This proportion is a critical threshold and is crucial in their approach...
  • Data Science For Business: NYC Media Lab Interview With Foster Provost

    We had the opportunity to engage in a discussion with Foster Provost (NYU Stern) about the value of sharing data knowledge across an organization, leveraging data as a strategic asset, and privacy implications, among other points. He also took us through a crash course on some of the fundamental concepts behind data science. What follows is an edited version of our transcripted conversation...
  • Using Deep Learning To Listen For Whales

    While most attention [in neural networks] has gone into the problem of using convnets to do image recognition, in this article I will describe how I was able to successfully apply convnets to a rather different domain, namely that of underwater bioacoustics, where sounds of different animal species are detected and classified...
 
 

Data Science Articles & Videos

 
  • Josh Wills (Cloudera): Presentation On The Life Of A Data Scientist
    The current talent scarcity means that we need to identify and develop people with backgrounds in either statistics, software engineering, or scientific research into successful data scientists. We will discuss how to grow data scientists as well as data science teams, and how to build the kind of work environment that data scientists love...
  • Data Science – The Foundation For Leading Banks
    Now-a-days the Banking Industry is facing many challenges - rapidly changing consumer environment, rigorous regulatory guidelines, highly competitive environment, emergence of new channels to name a few. With these great challenges come great rewards—Banks have the opportunity to pull ahead of the curve or completely fall behind. Accurately applying Data Science will separate the leaders from the followers...
  • Machine Learning To Process, Analyze Video Content
    Its no secret that we have too much data to ever process ourselves. To add to this, there will soon be a whole new explosion of data to deal with in the form of video. As wearable technology products such as Google Glass become mainstream we'll collectively add millions of hours of video content to the blogs, buying patterns, Instagrams and tweets we already generate - and computers are set to step in and do the sifting...
  • Building A Data Science Community: Harlan Harris Interview (DC2 Founder)
    We recently caught up with Harlan Harris, Co-Founder and current President of Data Community DC (DC2). After multiple years (and degrees!) in academia he transitioned to industry as a Data Scientist in 2009. We were keen to learn more about his background, the vision for DC2 and his views on how Data Science is evolving ...
  • Understanding The Consumer Journey Through Location Data
    Duncan McCall is currently the CEO and Co Founder of PlaceIQ, a leading provider of location intelligence, enabling advertisers to reach and define mobile brand audiences at scale for a wide range of marketing activities. Duncan’s background includes leading or being part of the executive team for a number of startups from the location, mobile and internet arena. The Makegood recently spoke with Duncan about understanding the consumer journey through location data...
  • Kira Radinsky Is An Internet Oracle
    Dr. Kira Radinsky can see into the future. The girl who landed a spot on MIT’s prestigious 35 Innovators Under 35 list this year—previous winners include nerds like Facebook’s Mark ­Zuckerberg—has figured out a way to forecast natural disasters, disease epidemics, social unrest, and violence outbreaks. But she's no Miss Cleo. Her predictions aren’t vague or ambiguous. They are made of something much more concrete—science. Kira is pioneering predictive data-mining software for Technion-Israel Institute of Technology...
  • Data Scientist Job Explained, How It Works, Misconceptions Debunked
    This is a very good video as we hear the buzz words and big data right and left all the time. These 2 data scientists are pretty much off the cuff and talk about how they work in the real world. Both of these folks are from SAP and talk about their backgrounds and how they both somewhat morphed into the job...
 
 

Jobs

 
  • Data Science for Social Good, Summer 2014 Fellowship, Chicago

    The Eric & Wendy Schmidt Data Science for Social Good fellowship is a University of Chicago summer program for aspiring data scientists to work on data mining, machine learning, big data, and data science projects with social impact. Now accepting applications...
 
 

Training & Resources

 
  • 16 Free eBooks On Machine Learning!

    Those involved in the field of Robotics and Artificial Intelligence are well aware of 'Machine Learning'. Here we bring to you 16 ebooks on the discipline, which are free to read and download!...
  • Data Science in Python

    Last September we gave a tutorial on Data Science with Python at DataGotham right here in NYC. The conference was great and I highly suggest it! The "data prom" event the night before the main conference was particularly fun! We've published the entire tutorial as a collection of IPython Notebooks. You can find the entire presentation on github or checkout the links here...
  • Finding The K In K-Means Clustering
    The basic k-means is an extremely simple and efficient algorithm. However, it assumes prior knowledge of the data in order to choose the appropriate K. Other disadvantages are the sensitivity of the final clusters to the selection of the initial centroids and the fact that the algorithm can produce empty clusters. In today’s post, and by popular request, we are going to have a look at the first question, namely how to find the appropriate K to use in the k-means clustering procedure...
  • Create Real-Time Graphs With PubNub And D3.js

    Graphs make data easier to understand for any user. Previously we created a simple graph using D3.js to show a way to Build a Real-Time Bitcoin Pricing and Trading Infrastructure. Now we are going to dive a bit deeper with the power of D3.js, showing how graphs on web pages can be interactive and display an array of time plot data using a standard Cartesian coordinate system in an easily understandable fashion...
 
 
P.S. Did you enjoy the newsletter? Do you have friends/colleagues who might like it too? If so, please forward it along - we would love to have them onboard :)
 
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