Every two weeks, we find the most interesting data science links from around the web and collect them in Data Science Briefings, the DataMiningApps newsletter. Subscribe now for free if you want to be the first to get up to speed on interesting resources.
- The Evolution of Trust
Nicky Case does it again with a fantastic explorable explanation on game theory. The concepts are well known, but he manages to link it to another fundamental question: why do we trust others less today?
- A.I. and Big Data Could Power a New War on Poverty
When it comes to artificial intelligence and jobs, the prognostications are grim.
- Face2Face: Real-time Face Capture and Reenactment of RGB Videos
“Our goal is to animate the facial expressions of the target video by a source actor and re-render the manipulated output video in a photo-realistic fashion.”
- 10 AI Failures in 2017
“This year artificial intelligence programs AlphaGo and Libratus triumphed over the world’s best human players in Go and Poker respectively. While these milestones showed how far AI has come in recent years, many remain sceptical about the emerging technology’s overall maturity — especially with regard to a number of AI gaffes over the last 12 months.”
- My favorite deep learning papers of 2017
“Even with so many deep learning papers coming out this year, there were a few publications I felt managed to rise above the rest. Here are the five papers that impacted my mental models the most over the last year. For each, I state the “goal” of the paper, briefly summarize the work, and explain why I found it so interesting.”
- Deep learning sharpens views of cells and genes
Neural networks are making biological images easier to process.
- AI and Deep Learning in 2017 – A Year in Review
“Looking back through my Twitter history and the WildML newsletter, the following topics repeatedly came up.”
- Most Read Data Science Articles of 2017
“As the year end approaches we decided to dig through the 2017 archives to figure out what were the most read articles of the year.”
- Architecture of Giants: Data Stacks at Facebook, Netflix, Airbnb, and Pinterest
Because their products have massive adoption, these teams must continuously redefine what it means to do analytics at scale. They’ve invested millions into their data architectures, and have data teams that outnumber the entire engineering departments at most companies.
- Predicting Crime in SF- a toy WMD
“When new technologies emerge, our ethics and our laws normally take some time to adjust. As a social scientist and a philosopher by training, I’ve always been interested in this intersection of technology and morality. A few months ago I read Cathy O’Neil’s book Weapons of Math Destruction and realized its message was too important yet neglected by data scientists.”
- How an A.I. ‘Cat-and-Mouse Game’ Generates Believable Fake Photos
“The woman in the photo seems familiar. She appears to be a celebrity, one of the beautiful people photographed outside a movie premiere or an awards show. And yet, you cannot quite place her. That’s because she’s not real. She was created by a machine.”
- The State of Data Science & Machine Learning, 2017
Kaggle conducted an industry-wide survey to establish a comprehensive view of the state of data science and machine learning.
- How far ahead of Apple Maps is Google Maps?
“Google has said surprisingly little about how it’s making AOIs—just that they’re generated using an “algorithmic process” that identifies “areas with the highest concentrations of restaurants, bars and shops”.”
- What’s hidden in the hidden layers?
A throwback to an article from 1989… so old, yet so familiar.