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Introducing a new #Python package called mapwidget - creating interactive 3D maps in a Jupyter environment using popular JavaScript libraries, such as #CesiumJS, #Mapbox, #MapLibre, #Leaflet, and #OpenLayers GitHub: #geospatial #gischat #anywidget

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Qiusheng Wu

51,307 subscribers

154,871 Aufrufe • vor 3 Jahren •via X (Twitter)

#Python#CesiumJS#Mapbox#MapLibre#Leaflet#OpenLayers#geospatial#gischat#anywidget
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10 Kommentare

Profilbild von Qiusheng Wu
Qiusheng Wuvor 3 Jahren

The mapwidget Python package is built upon the #anywidget pacakge by @trevmanz. Thank you for making it so much easier to build Jupyter widget from JavaScript libraries.

Profilbild von Qiusheng Wu
Qiusheng Wuvor 3 Jahren

Note that mapwidget has bidirectional communication. You can pass data from JavaScript back to Python for further processing, e.g., getting map center, bounds, zoom level. Try it out 👇

Profilbild von Julio
Juliovor 3 Jahren

Great news! Thank you

Profilbild von Antony.Barja
Antony.Barjavor 3 Jahren

Maplibre ❤️

Profilbild von ul
ulvor 3 Jahren

amazing!!

Profilbild von Thepowerofgis
Thepowerofgisvor 3 Jahren

Nice one from Sifu... Amazing 3D view

Profilbild von Diego Chávez
Diego Chávezvor 3 Jahren

Awesome !

Profilbild von Archer
Archervor 3 Jahren

Good one

Profilbild von Amit Kokje Ph.D | अमित कोकजे
Amit Kokje Ph.D | अमित कोकजेvor 3 Jahren

Excellent, Thank you.

Profilbild von Danish Khan❄️
Danish Khan❄️vor 3 Jahren

Good work, keep it up

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Rebs Gaming

308,441 Aufrufe • vor 3 Jahren

Our first Generative AI short course in JavaScript! GitHub recently reported that JavaScript is again the world’s most popular programming language. To support web developers exploring and developing with generative AI, we just launched a new short course in JavaScript taught by Jacob Lee, founding engineer at . In ​​Build LLM Apps with LangChain.js you’ll learn elements common in AI development, including: (i) Using data loaders to pull data from common sources such as PDFs, websites, and databases (ii) Prompts, which are used to provide the LLM context (iii) Modules to support RAG such as text splitters and integrations with vector stores (iv) Working with different models to write applications that are not vendor-specific (v) Parsers, which extract and format the output for your downstream code to process You’ll also build with the LangChain Expression Language, which lets you easily compose sequences (also called chains) of modules to perform complex tasks using LLMs. Putting all this together, you’ll also work on a conversational question-answering LLM application capable of using external data as context. Please sign up here:
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Our first Generative AI short course in JavaScript! GitHub recently reported that JavaScript is again the world’s most popular programming language. To support web developers exploring and developing with generative AI, we just launched a new short course in JavaScript taught by Jacob Lee, founding engineer at . In ​​Build LLM Apps with LangChain.js you’ll learn elements common in AI development, including: (i) Using data loaders to pull data from common sources such as PDFs, websites, and databases (ii) Prompts, which are used to provide the LLM context (iii) Modules to support RAG such as text splitters and integrations with vector stores (iv) Working with different models to write applications that are not vendor-specific (v) Parsers, which extract and format the output for your downstream code to process You’ll also build with the LangChain Expression Language, which lets you easily compose sequences (also called chains) of modules to perform complex tasks using LLMs. Putting all this together, you’ll also work on a conversational question-answering LLM application capable of using external data as context. Please sign up here:

Andrew Ng

284,320 Aufrufe • vor 2 Jahren