ISSUE 260   ·   November 19, 2019        

Insight

A global survey of journalism and AI

This report from the Polis think-tank explores how AI is already being used in journalism and how newsroooms think about the implications. Given how fast the tech is moving, this is important work that spans 71 news organizations in 32 different countries.
Polis Blog at London School of Economics

13 Big Data Trends Industry Pros Are Watching

Every organization has their own use-cases, pain points and perspectives regarding data. In these interview snippets, data pros at 11 tech companies share insights from their corner of the data world.
Built In Blog

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Tools and Techniques

74 Summaries of ML and NLP Research Papers

These short summaries of Machine Learning and NLP research papers cover a wide variety of authors, topics and venues from the past couple of years. Includes key points, diagrams and links for each paper.
Marek Rei Blog

TileDB: A Database for Data Scientists

TileDB is a new database that's designed from the bottom-up for data science. This post explores key problems with current solutions and how TileDB's approach is a more effective way to store, update, analyze, and share large sets of diverse data.
TileDB Blog

An Introduction to Confident Learning

Confident Learning is an emerging field for characterizing label noise, identifying errors and learning using datasets with noisy labels. In this post, Curtis G. Northcutt describes what it is exactly, practical applications and how it works. This post also introduces a new open-source Python package for cleaning labels called the cleanlab.
L7 Blog

Advanced Training For CV Models: 3 Key Aspects Of Video Annotation

To maximize the potential in video data, there are 3 key aspects to consider when determining an approach: Entity Persistence, Detecting State Change, and Temporal Tagging. An enterprise-grade labeling platform that employs a holistic annotation approach can scale video annotation without diminishing complexity and compromising accuracy.
 Learn More.
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Resources

I haven't paid much attention to Microsoft since Windows 8 but I was at the Ignite Conference a couple weeks ago and there is a LOT that's worthwhile at Microsoft these days. Seriously. Along with the new HoloLens 2 and Project Silica, here are a few key resources that are worth checking out:

• AI Business School - Learn about AI strategy, responsibility, and technology through these online learning paths that are tailored to a  variety of industries.
• Azure Tips and Tricks - This collection of 230+ tips, videos and conference talks span the entire universe of the Azure platform.
• AI for Good - This site is the portal to Microsoft's AI for Good programs. Includes information about specific projects, apps, datasets, grants, research, etc. If you're interested in Tech for Good, this is a must-explore resource.

Data Viz

Why scientists need to be better at data visualization

The scientific literature is riddled with bad charts and graphs, leading to misunderstanding and worse. This post offers practical guidelines for choosing charts and colors to help others (and you!) understand your research. Includes lots of visual examples and common mis-perceptions.
Knowable Magazine

A network of science: 150 years of Nature papers

Beautiful presentation of the network of paper citations at Nature. This short video is nice introduction to the project. The interactive is here >>
Nature Channel on YouTube

Conferences & Events

Metis Webinar | AI ROI: The Questions You Need to Be Asking - As business leaders increase investment in advanced analytics, data science, and AI, many struggle to recognize a return on those efforts. During this free Metis Corporate Training webinar Kerstin Frailey, Senior Data Scientist and Head of Executive Corporate Training at Metis, will walk through what you need to ask before, during, and after the lifetime of a data science project. Thursday, December 5, 12pm ET

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Data Elixir is curated and maintained by @lonriesberg. For additional finds from around the web, follow Data Elixir on LinkedIn, Twitter or Facebook.