— In the News —
Complex systems can be inter-related in ways that defy standard mathematical analysis. This article explores the problems and a new approach based on chaos theory called “empirical dynamic modeling.” This approach doesn't start with models but instead, discovers the models from the system.
Google has been one of the biggest corporate sponsors of AI and has invested heavily in it for videos, speech, translation, and, of course, search. Here's an overview of the recently announced RankBrain, including a high-level view of how it works and how it fits into Google's search algorithms.
— Tools and Techniques —
Interactive map of the data engineering ecosystem, including descriptions, key trends, and links to the various tools and frameworks. Highly recommended.
Nice collection of statistical and machine learning concepts that are widely used and consistently useful in a large variety of domains and problem settings.
Tired of the Python versus R posts?! This is the second of a two-part tutorial that shows how to use them together.
In 2015, anything you see or read about a computer recognizing things in images or videos almost certainly involves a convolutional neural net. Among other things, this article by Andrej Karpathy offers an easy to understand explanation of how they work.
— Resources —
Raw Data is a new podcast out of Stanford that examines how big data and networked technologies are changing communities, the economy, politics and human behavior. The first few episodes have been great!
This collection of resources has only been available for a week and its GitHub repo already has over 600 stars. All levels are covered so regardless of how much experience you have, if you're interested in Deep Learning and NLP, you should definitely check this out.
— Career —
After making the jump from a postdoc in particle physics to a career in data science, Emily Thompson collected some answers for common concerns felt by academics wondering about the transition to industry. This is well-written and insightful.
— About —
Data Elixir is curated and maintained by @lonriesberg. If you find this newsletter worthwhile, please help spread the word! Forward to your colleagues or share on your favorite network: