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.
- There’s nothing magical about learning data science
The top 5 habits of a professional data scientist.
- What every data scientist should know about data anonymization
Interesting presentation on anonymization.
- Dreaming of names with RBMs
A classic problem in natural language processing is named entity recognition. Given a text, we have to identify the proper nouns. But what about the generative mirror image of this problem – i.e. named entity generation? What if we ask a model to dream up new names of people, places and things?
- Top-N tips for talking with non-Data Scientists
Cross-disciplinary work is hard, until you’re speaking the same language.
- 10 more lessons learned from building Machine Learning systems
Presentation at #mlconf 2015 in San Francisco.
- Design Better Data Tables
“After being the bread and butter of the web for most of its early history, tables were cast aside by many designers for newer, trendier layouts. But while they might be making fewer appearances on the web these days, data tables still collect and organize much of the information we interact with on a day-to-day basis.”
- A Unified Theory of Randomness
Researchers have uncovered deep connections among different types of random objects, illuminating hidden geometric structures.
- This startup uses machine learning and satellite imagery to predict crop yields
Artificial intelligence + nanosatellites + corn.
- Playing for Data: Ground Truth from Computer Games
“Recent progress in computer vision has been driven by high-capacity models trained on large datasets. Unfortunately, creating large datasets with pixel-level labels has been extremely costly due to the amount of human effort required. In this paper, we present an approach to rapidly creating pixel-accurate semantic label maps for images extracted from modern computer games.”
- NYC Subway Math
“Apparently MTA (the company running the NYC subway) has a real-time API. Let’s do some cool stuff with this data!”
- Machine Learning is Fun!
The world’s easiest introduction to Machine Learning
- How Vector Space Mathematics Reveals the Hidden Sexism in Language
As neural networks tease apart the structure of language, they are finding a hidden gender bias that nobody knew was there.
- Make Algorithms Accountable
Algorithms are ubiquitous in our lives. They map out the best route to our destination and help us find new music based on what we listen to now. But they are also being employed to inform fundamental decisions about our lives.
- Build Algorithms Like You Give a Damn
To make algorithms effective, we need effective communication.
- The AI That Cut Google’s Energy Bill Could Soon Help You
The same type of algorithm that beats humans at complex games is being applied in more practical areas.
- Researchers use neural networks to turn face sketches into photos
We all have a soft spot for Prisma, the app that turns smartphone photos into stylized artwork. But the reverse process — transforming artwork into pictures — is no less fascinating. And it’s not far from becoming real, researchers in the Netherlands said.