On Starting a New Job This blog post is a mixture of how to get into data science as well as how to leave academia for industry. I want to be clear that this is not my farewell letter to academia, but rather advice to other PhDs—especially in the social sciences—who are considering going into industrial data science.
Using Machine Learning to Expose Haters I wanted to use data science / machine learning to identify and rank haters by their “hater” level throughout the internet. I started with Hacker News and I wanted to explain the how and what I’ve done so far...
Foundations of Data Science [PDF] These notes are a first draft of a book being written by Hopcroft and Kannan (Microsoft Research) and in many places are incomplete. However, the notes are in good enough shape to prepare lectures for a modern theoretical course in computer science.
The Pothole Problem
Surely there is a more efficient way than having two chaps driving the motorways of the UK looking for holes in the ground? Couldn't the wonders of science, big data, machine learning, and perhaps the greatest thing on the Gartner hype cycle: the Internet of Things (IoT), come together in beautiful scientific and software symmetry to solve this glaring inefficiency?
Voices of Pro Bono Data Science: The Key
This is the first post in a four-part blog series highlighting voices of pro bono data science where we asked our volunteers and partner organizations to answer the question: "Why do you think pro bono data science can change the world?"
The NYU Center for Data Science invites applications for positions as Moore-Sloan Data Science Fellows. These positions are a prominent feature of the Moore-Sloan Data Science Environment at NYU, a multi-institutional effort funded in part by a generous grant from the Moore and Sloan Foundations...Appointments will be initially for two years, with an expectation of renewal for a third on satisfactory performance. Fellowships will be offered competitive salary and benefits, with funds to support research and travel. There is some flexibility about start date, but September 1, 2015 is expected.
On Being a Data Skeptic - Cathy O’Neil In this paper, I’ll make the case that the community of data practitioners needs more skepticism, or at least would benefit greatly from it, for the following reason: there’s a two-fold problem in this com‐ munity. On the one hand, many of the people in it are overly enamored with data or data science tools. On the other hand, other people are overly pessimistic about those same tools
Thanks to the increasingly efficient algorithms that power these sites, dating has been transformed from a daunting transaction based on scarcity to one in which the possibilities are almost endless...
As journalist Dan Slater shows, online dating is changing society in more profound ways than we imagine. He explores how these new technologies, by altering our perception of what’s possible, are reconditioning our feelings about commitment and challenging the traditional paradigm of adult life...
For a detailed list of books covering Data Science, Machine Learning, AI and associated programming languages check out our resources page.
P.S. Enjoyed the newsletter? Please forward it to friends and peers - we'd love to have them onboard too :-) - All the best, Hannah & Sebastian