ISSUE 324 ·   February 23, 2021        

Insight

Can Algorithms Learn to Fight Wars Ethically?

The U.S. Pentagon is spending a lot of money to develop advanced AI capabilities for the military. AI may be better at making fast decisions but when it comes to moral decisions, it could be a nightmare. There's a lot at stake and the issues are anything but black and white.
Washington Post

External data should be part of your data strategy

A 2018 report found that the most analytically mature organizations use a variety of data sources from outside of their organization. Third-party data is out there to find and use. Here's how to get started.
MIT Sloan School of Management

Sponsored Link

Virtual event: Using third-party data to make smarter decisions

Join this virtual event with Stephen Orban, author of Ahead in the Cloud and General Manager of AWS Data Exchange. He will lead a panel discussion with AWS customers to discuss the innovative techniques being used in data pipelines, with data analysis, and for data visualization. You will discover real-world initiatives and breakthroughs being enabled by third-party data.

Tutorials, Projects & Opinions

Data Mesh 101: Everything You Need To Know

Great starting point for understanding all the excitement about data meshes. Follow the links for some of the best resources that explain what data meshes are, how they're useful and how to get started.
Monte Carlo Data | Barr Moses

Create privacy-preserving synthetic data for machine learning with SmartNoise

Differential privacy promises significantly higher privacy protection than data anonymization techniques and it could be transformative in fields like medicine and economics. This post introduces the technique and how it's becoming the gold standard for data protection. Includes links to a detailed white paper and an open-source toolkit.
Microsoft Open Source Blog

Autodata: Automating common data operations

A lot of tasks in a data science workflow can be automated. In this post, Adam Marcus explores the landscape of open-source autodata tools and how it may evolve.
Adam Marcus

Patterns: Publishing cross-disciplinary data science outputs

There is more to data science than just the research article. Patterns publishes all the outputs of data science research including software, data sets, algorithms and infrastructures. Shine a spotlight on your work; submit your paper today.
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Code & Tools

MindsDB

MindsDB is a predictive AI layer for existing databases that allows you to develop, train and deploy state-of-the-art ML models using SQL queries. This project is growing fast and there's a lot to explore here.
GitHub | mindsdb

kglab: Graph-Based Data Science

The kglab package provides an abstraction layer in Python for building knowledge graphs. It leverages idiomatic Python for common use cases in data science and data engineering work that require graph data. If you're just getting started or need help, see the Resources section.
DerwinAI

Resources

DSPods

Nice collection of podcasts about data science, machine learning, and ML engineering. As of this morning, there are 24 active podcasts on this page, covering a wide range of topics. Updated daily.
DSPods

Data Visualization

D3 Turns 10

Ten years ago, the popular data viz library known as D3 was introduced to the world and empowered a new generation of experts to work with data in ways that weren't possible before. This anniversary post looks back at the stories and the people that brought D3 to life.  For a gallery and Getting Started guide, see the D3 tag in the Data Elixir Archives.
Observable | Melody Meckfessel

Data visualization using ggplot2 (intermediate)

Take your ggplot2 skills to the next level with these new workshop materials. This is well organized, includes a linked index, and there are lots of code snippets with screenshots to make it useful as a reference. For introductory materials, follow the links at the top.
RPubs | Ben Bond-Lamberty

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