Data Science Weekly - Issue 109
Issue #109 December 24 2015
Editor Picks
Child’s Play: Computers should stop trying to act like grown-ups
Thirty years of developmental cognitive science have shown that children are the best learners on earth. But how do they learn so much so quickly? For the last 15 years developmental cognitive scientists and computer scientists have been trying to answer this question, and the answers shape new kinds of machine learning...
The Star Wars Social Network
Some of us are looking forward to Christmas, and some of us are looking forward to the new film in the Star Wars franchise, The Force Awakens. Meanwhile, I decided to look at the whole 6-movie cycle from a quantitative point of view and extract the Star Wars social networks, both within each film and across the whole Star Wars universe...
Study Reveals Amazing Surge in Scientific Hype
Scientists are touting their research far more aggressively than they once did, according to a new study...
A Message from this week's Sponsor:
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Data Science Articles & Videos
What do we ask in Stack Overflow?
Stackoverflow is the biggest site of Q&A that means have a lot of data and fortunately we can get it - and generate some interesting insights on which programming languages on trending up and down...
Machine Learning: How Algorithms Get You Clicking
Technology may be able to free journalists from creating sensationalistic stories to generate online traffic, but it doesn't alter what people choose to read...
What We Talk About When We Talk About Iran
It goes without saying that global media perceptions of Iran are multivalent, myriad, and always evolving. To investigate those perceptions, in all their complexity, is a task for computational journalism. So in the spirit of inquiry, the Chartbeat Data Science Team tried to answer our original question, “How is Iran framed by the media?” with some good, old-fashioned computational analysis...
Accuracy vs Explainability of Machine Learning Models
My ex-labmate Ryan Turner presented an awesome poster at the NIPS workshop on Black Box Learning and Inference that was an eye-opener to me. Here I'm going to cover what I think was the main take-home message for me, but I encourage everyone to take a look at the paper for the details...
The difference between Superconnectors and everyone else:
Insights from 100,000 email introductions
Bonafide has amassed data from over 100,000 email introductions, allowing us to infer some meaningful patterns on who makes introductions, which people they introduce, and how and why they introduce them. We’ll be looking at behavior of top connectors in this post and then examining in more detail the dynamics of introductions in future posts...
A Year of Approximate Inference: Review of the NIPS 2015 Workshop
Probabilistic inference lies no longer at the fringe. The importance of how we connect our observed data to the assumptions made by our statistical models—the task of inference—was a central part of this year's Neural Information Processing Systems (NIPS) conference...
Why is there a need to manually implement machine learning algorithms when there are many advanced APIs like tensorflow available?
I am going to address this now from a different perspective: that of a company. Why would a company invest time and resources in implementing ML algorithms that already exist in the public domain?...
Baidu’s Deep-Learning System Rivals People at Speech Recognition
China’s leading Internet-search company, Baidu, has developed a voice system that can recognize English and Mandarin speech better than people, in some cases...
Deep-learning algorithm predicts photos’ memorability at “near-human” levels
Researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have created an algorithm that can predict how memorable or forgettable an image is almost as accurately as humans — and they plan to turn it into an app that subtly tweaks photos to make them more memorable...
What To Do When You Have Data Experience But Lack Job Specific Technical Skills
You have experience working with data but when you read job postings they all seem to want things you've never used or barely even heard of...
Jobs
Data Scientist - CitiBike - New York NYCBS seeks a Data Scientist to drive analytical work to help make Citi Bike the best bike share system in the world. Through empirical analysis and the development of customized software tools for staffing, rebalancing, maintenance and operations, the Data Scientist will help Citi Bike lead the global bike share industry in innovative, data driven approaches. The Data Scientist will report to the Operations Director and will work in tandem with Citi Bike Operations Managers to inform operational response, and develop best-practices for the organization...
Training & Resources
My top 5 ‘new’ Python modules of 2015
As I’ve been blogging a lot more about Python over the last year, I thought I’d list a few of my favourite ‘new’ Python modules from 2015. These aren’t necessarily modules that were newly released in 2015, but modules that were ‘new to me’ this year – and may be new to you too!...
Data Science End-to-End Walkthrough
In this walkthrough, you'll develop an end-to-end solution for predictive modeling using SQL Server R Services...
Deep Learning in a Nutshell: History and Training
This series of blog posts aims to provide an intuitive and gentle introduction to deep learning that does not rely heavily on math or theoretical constructs...
Books
Doing Math with Python Shows you how to use Python to delve into high school–level math topics like statistics, geometry, probability, and calculus...
"A book that is educational, fun and useful..."
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