Part 2 of the AI reading series. The previous post ended with AlexNet's 2012 earthquake in image recognition. This one tells the road to language: how researchers turned words into vectors, taught networks to read sequences, discovered attention — and why, in 2017, eight Google researchers decided attention was all you need.
The first in a reading series taking you from the artificial neuron of 1943 to today's transformers, mixture-of-experts models and agents. Lecture 1 is a preparatory guide to Cardon, Cointet and Mazières' sociological history of AI, with reading strategy and glossary.
Learn how to configure MetaMask for the Polygon Amoy testnet, claim free POL tokens and verify your transactions. Beginner‑friendly guide.
GeoPackage is an open and non-proprietary data format that allows different layers to be stored within the same file. In this post, we are going to read and save layers using python (geopandas) and R (sf).
R is an open-source statistical programming language used in statistical analysis but also in spatial analysis, artificial intelligence (AI), and machine learning (ML) applications. In this guide, we will walk you through the initial steps of setting up R and RStudio along with installing essential packages and testing them with spatial data.
In this guide you'll find clear instructions on setting up Python with Anaconda for spatial analysis. Then, we'll cover installing Python alongside Anaconda and adding essential dependencies like GeoPandas via the Anaconda Prompt. Lastly, we'll explore using the Jupyter Notebook for practical application.
