ISSUE 389  ·   May 31, 2022

Organizations

The technical pay gap

Ambiguous job tiles and overlapping responsibilities make it harder than ever to figure out what people should get paid. But some skills are harder to acquire and hone than others so people who can write code should make more than analysts, right? This is short and insightful.
Benn Stancil

Papers

Machine Learning for Sustainable Energy Systems

This review explores how machine learning has been used to facilitate the development and operation of sustainable energy systems. Covers current research, strengths and weaknesses of different approaches, and suggestions for future research and deployments.
Annual Review of Environment and Resources

Sponsored Link

The Data Team’s Guide for Marketing Metrics

Marketing leaders rely on data to meet their quarterly targets. Data teams can use this starter guide to better understand which metrics can accelerate marketing goals and increase ROI. Download Mode’s guide and put it into play with a 14-day Mode trial. 

Tutorials, Projects & Opinions

The Existential Threat of Data Quality

Data Quality remains an existential threat in virtually all data-driven organizations. Yet even as data stacks evolve, data quality problems seem to be getting worse. In this new series, Chad Sanderson explores the issues and how "ahead-of-the-curve" companies are responding.
Data Products | Chad Sanderson

In search of the least viewed article on Wikipedia

When Colin Morris went searching for Wikipedia articles that had even fewer views than the ones he wrote, he discovered 2 articles that had only 3 views each! The reason they have so few views is interesting and probably not what you'd expect. This is a fun and nerdy detective story.
Colin Morris

Build my open-source MLOps stack

This interactive tool explores the components of an MLOps stack. There are more than 50 tools here covering things like experiment tracking, data versioning, model serving, and much more. Select any tool to learn more about when to use it and things to watch out for.
My MLOps Stack

Visual essays explaining core ML concepts

Nice collection of interactive visualizations that are designed to teach machine learning theory and practical application. Topics cover decision trees, random forest, bias-variance tradeoff, double descent, and more.
AWS | MLU-EXPLAIN

DoubleCloud: make the most of your data in the cloud

DoubleCloud is a platform that helps organizations build cost-effective sub-second analytical applications on tightly integrated and proven open-source technologies like ClickHouse, Kafka and others. Preview for free with $500 in credits to get you started.
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Resources

Data Science in Context: Foundations, Challenges, Opportunities

This new book by an all-star cast of authors takes a broad look at data science in the world today. It starts out with a discussion of use-cases and then dives into a detailed discussion of the technical, societal, and ethical challenges that data scientists must navigate. Free to download.
Alfred Spector, Peter Norvig, Chris Wiggins, Jeannette M. Wing

Code & Tools

Villager

Villager is a framework for creating and running agent based models in R. Its purpose is to provide an extensible framework where modeling can be done in native R. It supports agents, agent aggregations and their associated resources, as well as flexible data management.
GitHub | Marcus Thomson

klassets

The klassets package is a collection of functions that simulate datasets to show how selected statistics models and machine learning algorithms work.
GitHub | Joshua Kunst

Data Visualization

Timely Advice – How Long Does Dataviz Take?

Everybody asks, “How long do you think that will take?” In this post, Eli Holder explores 10 data viz projects to show how much time goes into researching, data-wrangling, designing, and building different types of data visualizations. Includes retrospectives and advice along the way.
Nightingale | Eli Holder

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