Study of British place names: locations and frequencies of n-grams
:european_castle: Mapping British place names and other analysis - DanielJohnBenton/TownsAndVillages
Study of British place names: locations and frequencies of n-grams launched on August 10, 2017 with 5 votes and more than 50% of that year's launches. The site was still online in September 2026, 9 years on.
Does a similar job
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Free database of geographic place names and geospatial data2015 · github.com · ▲108Free database of geographic place names and corresponding geospatial data - delight-im/FreeGeoDB
- LWLearn where countries are on the world map with Spaced Repetition2025 · map.koljapluemer.com · ▲217
Hi HN, I made a web game to practice country locations a while ago and HN liked it, so I thought I'd post my updated version as well. As for how the game works and feels, I'd really recommend you checking it out for yourself, it's free, no signup, no ads. The tech stack is Vue + ts + Tailwind/Daisy for the looks. The learning algorithm is a slight modification of the ts version of FSRS. If you have anything to add, it's open source as well (https://github.com/koljapluemer/learn-worldmap), although not well documented yet. In the end it's just a little sideproject,…
- IMI made a little tool to practice country positions on the world map2023 · learn-worldmap.netlify.app · ▲45
Hi HN, I built a little tool to help me get better at remembering country locations on the map: https://learn-worldmap.netlify.app/ It's made from plain HTML/CSS/JS, and not intended to make any money or anything. Just thought that maybe someone else may enjoy it. Also of course happy about any feedback! Cheerz.
- M1Mapping 11M points with Tile38 – Mapbox/Geonames2018 · geonames.tile38.com · ▲51
Vicinity – Fast, Lightweight Nearest Neighbors with Flexible Back Ends2024 · github.com · ▲57We’ve just open-sourced Vicinity, a lightweight approximate nearest neighbors (ANN) search package that allows for fast experimentation and comparison of a larger number of well known algorithms. Main features: - Lightweight: the base package only uses Numpy - Unified interface: use any of the supported algorithms and backends with a single interface: HNSW, Annoy, FAISS, and many more algorithms and libraries are supported - Easy evaluation: evaluate the performance of your backend with a simple function to measure queries per second vs recall - Serialization: save and load your index for…
Lookup the school district associated with a street address in the US2024 · github.com · ▲58I wrote a tool in Python that finds the school district associated with any given street address in the United States. Here’s how it works: An address corresponds to a single point on the map. The U.S Census Bureau has a geocoder that converts an address to latitude and longitude coordinates. School district boundaries can be represented as polygons on the map. The National Center for Education Statistics (NECS) has geographic data on school district boundaries. Once we determine which polygon the point resides in, we know the school district.
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Source: Show HN post ↗
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