— In the News —
Great review of the current landscape of AI in healthcare by Eric Topol. This new article in Nature covers a lot of ground and is a must-read if you're interested in this space. Eric is a physician-scientist and is a bestselling author at the intersection of healthcare and technology.
It's an increasing concern that in many areas of science, published results are often impossible to reproduce. Here's how big data is undermining the science it enables.
— Insight —
As the founder and CEO of Fishtown Analytics, Tristan Handy has helped more than 100 VC-backed startups build their data teams. In this article, he explores how the structure of those teams is rapidly changing and what kind of support your data scientists and analysts really need. Includes specific suggestions, especially regarding engineering.
— Sponsored Link —
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— Tools and Techniques —
When Ben Weber started a new job as the Principal Data Scientist at Zynga last year, he took the opportunity to learn new tools. This post highlights some of the most useful ones he explored. Includes linked references to project pages and tutorials.
A lot happened in the world of machine learning in 2018. In this post, Emmanuel Ameisen from Insight Data takes a look at the key trends and shows where things are going in the coming year.
This advanced guide to Jupyter Notebooks offers a wide variety of tips, including things like useful shell and magic commands, logging, macros, running external code, extensions, enhancing visualizations, automated reporting, databases, and more.
Docker containers help to streamline your workflow and simplify reproducibilty. If you're new to Docker, here's a simple and well-organized introduction for using Docker with R.
Flair is a simple, open-source framework that delivers state-of-the-art performance for solving common NLP problems. This repository contains a set of tutorials and examples to help you get started.
Realize the promise of data analytics and find the opportunity in the numbers. The Master of Management Analytics from Smith School of Business is essential training to unleash the potential of data and generate competitive advantage.
— Resources —
This interactive book provides a practical introduction to deep learning. Concepts are introduced as they're needed and the suggested prerequisites are fairly modest. This resource goes along with an undergraduate course at UC Berkeley.
— Data Viz —
This repo includes the code, a demo and instructions for creating stunning visualizations of NOAA wind data. The visualizations are derived entirely from wind velocity data and the continents emerge organically from the differences in wind speed over water versus land.