Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...

In recent years, numerous landslides on hillsides in urban and rural areas have underscored that understanding and predicting these phenomena is more than an academic curiosity—it is a human necessity ...

How to model a pendulum in Python using Jupyter Notebooks. This video walks through the physics of pendulum motion and shows how to simulate it step by step with clean Python code and clear ...

Organizations have a wealth of unstructured data that most AI models can’t yet read. Preparing and contextualizing this data is essential for moving from AI experiments to measurable results. In ...

Remotely sensed geospatial data are critical for applications including precision agriculture, urban planning, disaster monitoring and response, and climate change research, among others. Deep ...

According to @DeepLearningAI, it launched a short course titled Jupyter AI: AI Coding in Notebooks, taught by Andrew Ng and Brian Granger, that trains users to generate code, debug errors, and get ...

What if the vast, intricate web of planetary data could be transformed into insights that save lives, protect ecosystems, and shape the cities of tomorrow, all in real time? For decades, analyzing ...

Artificial intelligence has developed rapidly in recent years, with tech companies investing billions of dollars in data centers to help train and run AI models. The expansion of data centers has ...

License: The code in this repository is licensed under the Apache License, Version 2.0. Digital Earth Africa data is licensed under the Creative Commons by Attribution 4.0 license. Contact: If you ...

This Futures Lab series uses big data and geospatial analysis to uncover how authoritarian states and non-state actors carryout gray zone operations, and explores how innovative analytic methods can ...