We delved into New York using POI data, revealing social insights and business trends:

Starbucks strategically clusters near transport hubs. Dunkin Donuts dominates. Rockefeller Center is busy Mondays, Times Square surges. Cultural expressions in Jamaica and China. Gucci outlets align with luxury zones.

For more information, https://hirinfotech.com/points-of-interest-datasets/ or contact us at [email protected]

Statistics is a common language of all data explorations happening around us.

Citizen Gain: Exploring Data for Systems Change | Tackle the limitations of public data

Delve into the power of data for societal transformation! Join us in "Citizen Gain" as we navigate through the challenges and possibilities of leveraging public data for meaningful systems change. Uncover insights, tackle limitations, and discover the potential to reshape our communities through informed action.

Navigating the Data Landscape: Tools and Techniques for Effective Analytics

"Embark on a data exploration journey with our latest guide, 'Navigating the Data Landscape: Tools and Techniques for Effective Analytics.' 🚀 Discover the power of cutting-edge tools and innovative techniques that streamline your Data analytics process. 📊🔍 Stay ahead in the data game and bookmark this resource for quick access to insights that drive success. 🌐

🌈 Explore the nuances of causation and correlation in the marketing world. Share your thoughts on the intricate dance between data and strategy.

Today, KnowledgeHound, the only search-based analytics solution in the world designed for survey data, announced the release of its most-requested product, which is called Rapid Reports. Whether you need full crosstabs or want to zoom in on a specific visualization of your data, Rapid Reports by KnowledgeHound is designed to fit into your existing workflow. This is the case whether you need full crosstabs or not.

Huh, this is a pretty cool idea. They want to figure out the internal representation in a large language model, in this case to find some internal state that classifies sentences as true or false. But how do you fish that out of the five thousand-element vector at a given layer?

Well, they feed it a ton of sentences which look exactly the same except that some are true and some are false: 　The city of Kyoto is in Japan 　The city of New York is in India 　The city of Gold Coast is in China 　etc etc and do PCA on the resulting vectors. Since the only variation is in the true/false values, they get two principal components that separate true and false sentences. Then if you project other sentences like "Quinoa is not a grain but actually a cabbage" or "the domestic dog is the most common pet in the world" into the same basis, they still fall into the same true/false regions.

The Geometry of Truth: Do LLM's Know True and False

https://saprmarks.github.io/geometry-of-truth/dataexplorer/

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Data Exploration of the Sloan Digital Sky Survey Data explorations examining the correlations between various wavelengths of light from galaxies, stars and quasars. Model made with Random Forest classifier.

Data from the Sloane Digital Star Survey

library(DataExplorer) plot_correlation(df)

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The KnowledgeHound Data Pipeline has finally made its debut, and we at KnowledgeHound couldn’t be happier to make the announcement. A data pipeline for collecting consumer data that has been built with the data from your market research in mind especially. The KnowledgeHound Data Pipeline will make it possible for marketers to collect, clean, organize, and integrate an enterprise’s survey data by leveraging our Application Programming Interfaces (APIs).