Data Elixir - Data Elixir - Issue 368
ISSUE 368 · January 4, 2022Happy New Year! 🎉 To start off the year, please take 3 minutes and answer a few questions that will help guide the content of Data Elixir for 2022. Help make Data Elixir more useful for you --> Thanks! InsightThe Case Of The Abandoned MetricsThe world we see is largely painted by numbers these days and so the numbers have become politicized. But be careful. "Changing our metrics to suit our narratives has caused confusion, frustrated the honest, and destroyed public trust..." Sponsored LinkFree Course: Natural Language Processing (NLP) for Semantic SearchLearn how to build semantic search applications! This free course from Pinecone covers everything you need to build state-of-the-art language models for semantic search. Start reading→ Tutorials, Projects & OpinionsWays I Use Testing as a Data ScientistWriting tests is more than just making sure your code works. Here are practical ways to think about and approach testing for different types of code and data. With examples and links to key resources along the way. Real-time machine learning: challenges and solutionsAlthough mainstream adoption of continual learning is still a few years away, there's a lot you can do now. In this post, Chip Huyen explores the challenges and solutions for online prediction and continual learning, with step-by-step use cases, considerations, and examples. PostHog - Host Your Own Product AnalyticsPostHog is the all-in-one platform for building better products. Heatmaps, funnel analysis, feature flags, session replays and more in one powerful, open-source platform. Try PostHog today for free, with no time limits. Code & ToolsETNA Time Series LibraryETNA is an easy-to-use time series forecasting framework that includes built-in toolkits for time series preprocessing, feature generation, and a variety of predictive models, from classic machine learning to SOTA neural networks, models combination methods and smart backtesting. ZinggZingg is an ML based tool that provides scalable data mastering, deduplication and entity resolution. Resources⚽ Analytics 2021 ReviewAwesome roundup of ⚽ analytics content from 2021. Covers research papers, blog posts, podcasts, webinars, and more! 📺 ML YouTube CoursesHere are some of the best and most recent machine learning courses that are available on YouTube. If you're not already familiar with courses on YouTube, the quality of the content may surprise you. There are a wide variety of ML courses here, ranging from introductory to advanced from Stanford, UC Berkeley, CMU, UMass, NYU, and MIT. Data Visualization100 Beautiful and Informative Notebooks of 2021Nice selection of top Observable notebooks, covering a wide range of topics in things like mathematics, sports, science, maps, tutorials, and much more. This is worth skimming first and then pick a few projects to dive into later. There's a lot here that's worthwhile. Science visualization trends of 2021Helena Jambor went through a collection of 2021 Nature articles and distilled 10 key visualization trends. This is well organized and includes screenshots, clear descriptions, and links to key resources. To find specific content from prior issues or to research topics, check out the searchable Archives on Data Elixir's Search Page >> |
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Data Elixir - Issue 367
Tuesday, December 21, 2021
Top Python libraries in 2021. Essential visualization. Jupyter games. Life of an ML dataset. Data versioning.
Data Elixir - Issue 366
Tuesday, December 14, 2021
Big data paradox. Data "scientists"...? ML playgrounds. Data serialisation in R. Building models like open-source software.
Data Elixir - Issue 365
Tuesday, December 7, 2021
Consulting rates for DS. Tidy/Pandas visual tutors. State of Open Data. Unit testing in R. Mining the Pandora Papers.
Data Elixir - Issue 364
Tuesday, November 30, 2021
Shuffling the cloud. Data for good, responsibly. Decision tree viz. Longform NLP pipelines. Controlling the job hunt.
Data Elixir - Issue 363
Tuesday, November 23, 2021
Transformers from scratch. Open-source experiment tracker. Parameter exploration w/ Bayesian Optimization. Confidential computing.
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