Data Science Weekly - Issue 127
Issue #127 April 28 2016
Editor Picks
Sorry ARIMA, but I’m Going Bayesian
When people think of “data science” they probably think of algorithms that scan large datasets to predict a customer’s next move or interpret unstructured text. But what about models that utilize small, time-stamped datasets to forecast dry metrics such as demand and sales? Yes, I’m talking about good old time series analysis, an ancient discipline that hasn’t received the cool “data science” rebranding enjoyed by many other areas of analytics...
China Is Building a Robot Army of Model Workers
Can China reboot its manufacturing industry—and the global economy—by replacing millions of workers with machines?...
How Information Graphics Reveal Your Brain’s Blind Spots
We’re only at the very beginning of taking advantage of the ways graphics and visuals reveal our mental errors, our biases, our very bizarre behavior and our blind spots — to our own minds and to the situations of other people. I believe interactives, especially “you do it” graphics, can help. But given the length of this list, I suspect we’re going to be busy at it for a while...
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Data Science Articles & Videos
Computers That Crush Humans at Games Might Have Met Their Match: ‘StarCraft’
Artificial intelligence has conquered complex games, but to win this one, machines need to figure out how to lie...
10 Questions for the Nation’s First Chief Data Scientist
DJ Patil reflects on his first year as chief data scientist in the White House’s Office of Science and Technology Policy...
The Race For AI: Google, Facebook, Amazon, Apple In A Rush To Grab Artificial Intelligence Startups
More than 20 private companies working to advance artificial intelligence technologies have been acquired in the last 3 years by corporate giants competing in the space, including Google, Amazon, Apple, IBM, Yahoo, Facebook, Intel, and, more recently, Salesforce. There have been 4 major acquisitions already in 2016...
What Happens When Baseball-Stats Nerds Run a Pro Team?
In 2015, the Sonoma Stompers, the team with one of the lowest payrolls in the Pacific Association, a professional baseball league near San Francisco, did something desperate: It handed its baseball-operations department to a couple of stat-savvy writers with no baseball-management experience, Ben Lindbergh and me...
A neural network groups scenes from different films by setting
GoogleNet DeepLearning neural net groups scenes from different movies by setting ...
Let there be Color!: Joint End-to-end Learning of Global and Local Image Priors for Automatic Image Colorization with Simultaneous Classification
We present a novel technique to automatically colorize grayscale images that combines both global priors and local image features. Based on Convolutional Neural Networks, our deep network features a fusion layer that allows us to elegantly merge local information dependent on small image patches with global priors computed using the entire image...
I'll Keep Using R
During my two years at Texas State, I’ve been engaged in a bit of an experiment on statistics & data analysis tools...
Algorithm Visualization
We've kicked off a series of algorithm coding katas at work. As something of an algorithms and data viz geek I thought I'd take part...
Jobs
Data Scientist - FanDuel - New York, NY FanDuel is the pioneer of online daily fantasy sports, one of the fastest growing sectors of the sports and entertainment industry. The Data Scientist will be responsible for answering the biggest, toughest and most interesting questions facing the company: How do we optimize revenue? Who are our “best” customers? How should we best spend our marketing budget? As an expert in machine learning, optimization and statistics you will apply your talents across all business areas, implement your findings, and make a great product even better for all our customers. This role requires a unique blend of business understanding and technical expertise – and the ability to communicate the outputs of difficult calculations in a way that’s clear, concise and unambiguous....
Training & Resources
Spreadsheet Thinking vs. Database Thinking
The shape of a dataset is hugely important to how well it can be handled by different software. The shape defines how it is laid out: wide as in a spreadsheet, or long as in a database table. Each has its use, but it’s important to understand their differences and when each is the right choice...
D3 Zoom for SVG Lines and SVG Paths
This video covers D3 Zoom for SVG Lines and SVG Paths...
bayes.js - MCMC and Bayes in the browser
bayes.js is small toy JavaScript MCMC framework that can be used fit Bayesian models in the browser. I call it "toy" because I would use it for fun, but not in production...
Books
Python Crash Course: A Hands-On, Project-Based Introduction to Programming Thorough introduction to programming with Python...
"I have read multiple beginner guides to Python. I am currently up to chapter 11 in Python Crash Course. So far this is far and away my favorite Python programming book..."
For a detailed list of books covering Data Science, Machine Learning, AI and associated programming languages check out our resources page.
P.S. Interested in reaching fellow readers of this newsletter? Consider sponsoring! Email us for details :) - All the best, Hannah & Sebastian