Data Elixir - Data Elixir - Issue 395
ISSUE 395 · July 12, 2022TrendsData teams are getting larger, fasterData teams are getting bigger, faster but something happens when a team grows past 10 people. You no longer know if the data you use is reliable, the lineage is too large to make sense of and end-users start complaining about data issues every other day. In his latest post, Mikkel Dengsøe explores the issues and ways to handle them as a team scales. In the NewsHow likely is it that the audits of Comey and McCabe were a coincidence? A statistical exploration.It's not often that a news source will teach statistics to expose a story. But without the statistics, you're just left with accusations that could be easy to brand as fake news. How likely is it that the audits were a coincidence? The answer is harder to determine than you might think. Sponsored LinkDoubleCloud: make the most of your data in the cloudCollect, aggregate and migrate data from multiple sources to build sub-second analytics on fully managed data stacks with proven open-source technologies. Perfect solution for unlocking the potential in your data. Start your trial today Tutorials, Projects & OpinionsSuccess Metrics for Product AnalyticsGreat post on success metrics and how ultimately, they're not a replacement for strategy. They're a way to confirm that the strategy was executed successfully. 4 Pandas Anti-Patterns to Avoid and How to Fix Thempandas users often learn suboptimal coding practices that become their default workflows. This post highlights four common pandas anti-patterns and outlines a set of techniques that you should use instead. MLOps: Overview, Definition, and ArchitectureGreat overview of Machine Learning Operations (MLOps) based on a mixed-method research approach, including a literature review, a tool review, and expert interviews. This is a wide-ranging paper that covers MLOps principles, components, roles, architecture, and workflows. There's a lot that's still being figured out in MLOps but for anyone who might think MLOps is simple, check out Figure 4! ResourcesPython for Data Analysis, 3rd EditionThe third edition of Wes McKinney's Python for Data Analysis has just been released and is free to read online. This is a practical, hands-on guide for manipulating, processing, cleaning, and analyzing datasets with Python. This new edition brings the content up-to-date from 2017. Data in WonderlandStorytelling can enhance others' understanding of data, especially when combined with analysis and visualization. In this online book, Scott Spencer shows how — covering everything from writing style to visualization & interactives to how to give a good presentation. Data VisualizationCareer Portraits in Data VisualizationA lot of people are involved in producing data visualizations. Among analysts, designers, developers, and engineers — who does what, exactly? And what are their backgrounds? This is a great deep dive, based on the Data Visualization Society's "State of the Industry" survey. Multi-scale model assessment with spatialsampleNice tutorial that shows how (and why!) to use the new {spatialsample} rstats package to model spatially structured data. OutlierUsing GPT-3 to explain how code worksAwesome use-case for GPT-3. Could GPT-3 really explain how sections of code work? Check this out. "It’s shockingly effective." Was this email forwarded to you? Sign up here >> |
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Data Elixir - Issue 394
Tuesday, July 5, 2022
Causal forecasting. ML exercises for pen and paper. Mixed effects models tutorial. Geo-based A/B testing.
Data Elixir - Issue 393
Tuesday, June 28, 2022
What Julia gets right. ML stack trends. Scraped data: fair game? Things you should know about DBs. Investment research platform for DS.
Data Elixir - Issue 392
Tuesday, June 21, 2022
Graph ML intro. JTBD for data teams. How to get data out of PDFs. Research highlights from Meta. Reproducible research workflows.
Data Elixir - Issue 391
Tuesday, June 14, 2022
ML design patterns. Awesome data leadership. Faster Pandas. ML experimentation in VS Code.
Data Elixir - Issue 390
Tuesday, June 7, 2022
Friendlier SQL. Decision Intelligence framework. Collective data rights.
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