Data Elixir - Data Elixir - Issue 389
ISSUE 389 · May 31, 2022OrganizationsThe technical pay gapAmbiguous 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. PapersMachine Learning for Sustainable Energy SystemsThis 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. Sponsored LinkThe Data Team’s Guide for Marketing MetricsMarketing 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 & OpinionsThe Existential Threat of Data QualityData 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. In search of the least viewed article on WikipediaWhen 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. Build my open-source MLOps stackThis 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. Visual essays explaining core ML conceptsNice 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. DoubleCloud: make the most of your data in the cloudDoubleCloud 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. ResourcesData Science in Context: Foundations, Challenges, OpportunitiesThis 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. Code & ToolsVillagerVillager 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. klassetsThe klassets package is a collection of functions that simulate datasets to show how selected statistics models and machine learning algorithms work. Data VisualizationTimely 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. Was this email forwarded to you? Sign up here >> |
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Data Elixir - Issue 388
Tuesday, May 24, 2022
Software development for DS. How random forests really work. Visualizing multicollinearity. ML for conservation.
Data Elixir - Issue 387
Tuesday, May 17, 2022
Supervised clustering. Bandits for recommender systems. JavaScript for R. Teaching data science at scale.
Data Elixir - Issue 386
Tuesday, May 10, 2022
Trusting your data. How to protect your models. How to hire for DS roles. Horizon charts.
Data Elixir - Issue 385
Tuesday, May 3, 2022
Making data actionable. Using BIG AI models in a startup. From academia to industry. ML validity. Mental models for visualization.
Data Elixir - Issue 384
Tuesday, April 26, 2022
Data tests. Null Island. Confidence intervals for ML classifiers. Containers for ML. Performance utilities for regression modeling.
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