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.
- Silicon Valley siphons our data like oil. But the deep drilling has just begun
Personal data is to the tech world what oil is to the fossil fuel industry. That’s why companies like Amazon and Facebook plan to dig deeper than we ever imagined. - A Survey of 3,000 Executives Reveals How Businesses Succeed with AI
“The next digital frontier is here, and it’s AI.” - Scraping data from the public web may be legal
When is it okay to grab data from someone else’s website, without their explicit permission? A new ruling by a federal judge in California might have dramatic implications on this question, and on the open nature of the web in general. - Data Alone Isn’t Ground Truth
You should always carry a healthy dose of skepticism in your back pocket. - To Survive in Tough Times, Restaurants Turn to Data-Mining
“According to the tech wizards who are determined to jolt the restaurant industry out of its current slump, information culled and crunched from a wide array of sources can identify customers who like to linger, based on data about their dining histories.” - How the GDPR will disrupt Google and Facebook
Google and Facebook will be disrupted by the new European data protection rules that are due to apply in May 2018. This note explains how. - Machine Learning for Humans
Simple, plain-English explanations accompanied by math, code, and real-world examples. - Why We Need Accountable Algorithms
AI and machine learning algorithms are marketed as unbiased, objective tools. They are not - Support Hypothesis
In September, Stripe is supporting the development of Hypothesis, an open-source testing library for Python created by David MacIver. Hypothesis is the only project we’ve found that provides effective tooling for testing code for machine learning, a domain in which testing and correctness are notoriously difficult. - Cornea AI aims to predict the popularity of your next photo
The Cornea score uses Artificial Intelligence to predict the popularity of your photo. - Logo Rank is an AI system that understands logo design
It’s trained on a million+ logo images to give you tips and ideas. It can also be used to see if your designer took inspiration from stock icons. - ggpage
Creates Page Layout Visualizations in R - Can CNNs transliterate Pinyin into Chinese characters correctly?
This project examines how well neural networks can convert Pinyin, the official romanization system for Chinese, into Chinese characters. - Simulate colorblindness in R figures
This new R package provides a variety of functions that are helpful to simulate the effects of colorblindness in R figures. - PyTorch or TensorFlow?
“This is a guide to the main differences I’ve found between PyTorch and TensorFlow.” - Deep Learning is not the AI future
“While Deep Learning had many impressive successes, it is only a small part of Machine Learning, which is a small part of AI. We argue that future AI should explore other ways beyond DL.”
