ChatGPT GIS GeoSpartial Analysis Tutorial
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ChatGPT GIS GeoSpartial Analysis Tutorial

In this tutorial, you will learn how to use ChatGPT, which is large language model developed by OpenAI, to perform GIS/geospatial analysis.

By Futurology AR

Date and time

Tuesday, April 29 · 12 - 1am PDT

Location

Online

Refund Policy

Refunds up to 7 days before event

About this event

  • Event lasts 1 hour

In this tutorial, you will learn how to use ChatGPT, which is large language model developed by OpenAI, to perform GIS/geospatial analysis.

We will be exploring the capabilities of ChatGPT as a helpful assistant in providing very specific answers to geospatial analysis related questions in the form of Python code snippets.

This tutorial consists of six examples which covers a wide array of geospatial analysis and visualization examples such as importing shapefiles using GeoPandas library, displaying shapefiles using Matplotlib library, performing intersection operations, calculating buffer zones, calculating distances between points, exporting results into CSV files and so much more.

To demonstrate these examples, we are using a Jupyter notebook, however you would be able to follow along the tutorials using any IDE of your choice, as long as you make sure you are equipped with the external Python libraries that we would be using to perform these geospatial analysis tasks.

ChatGPT is a conversational Artificial Intelligence (AI) language model developed by OpenAI that uses deep learning to generate human-like text based on input prompts. In the field of Python programming, ChatGPT can be used to generate code snippets and provide suggestions on how to solve coding problems.

The model's vast knowledge base, obtained through its training on a massive corpus of text data, allows it to quickly generate relevant and accurate code.

This can be especially useful for developers who need to quickly prototype ideas or debug issues in their code.

Furthermore, ChatGPT is also able to provide suggestions and alternatives for different approaches to solving coding problems, allowing developers to make informed decisions about the best course of action for their project.

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