April 14, 2024

Rohit Pandey · Follow Published in Towards Data Science · 11 min read · 3 hours ago — Image created with midjourney Motivation for open data At the risk of stating the obvious, the biggest weakness of a data scientist is that they can’t practice their craft without high quality data. And creating a high quality dataset isn’t exactly trivial. This becomes the most obvious blocker to adding any kind of value via this discipline.

Image created in Canva by the author How to implement a caching mechanism in Python, and when not to use it? Christopher Tao · Follow Published in Towards Data Science · 9 min read · 3 hours ago — When talking about improving Python execution performance, especially for data processing, there are too many 3rd party libraries that can help us. If we think about their mechanisms, most of them rely on optimising the…

The Essentials of the Spatial Error Model (SEM) Leonardo Maldonado · Follow Published in Towards Data Science · 5 min read · 3 hours ago — Images created by using AI tools such as Photo Realistic GPT and Super Describe. Remote sensing, a field that deals with tons of spatial data extracted and processed from satellite images, aerial photos, and other sensor-based technologies, or any field using data with spatial features, presents a non-trivial challenge.

The Untapped Potential of Neuron-State Data Sara Nóbrega · Follow Published in Towards Data Science · 11 min read · 3 days ago — Image by author. Have you ever wondered if there’s a better way to spot what doesn’t belong in a set of image data? Traditional methods have their place, but what if the key to a more refined approach lies within the model itself — specifically, in the state of its neurons?