It turns out, focusing on “the fundamentals” first is a great way to never get started at all.
The Potential of Generative Adversarial Networks (GANs) in Data Science
Generative Adversarial Networks (GANs), introduced in 2014, have significantly advanced AI by creating realistic images and data, impacting fields from art to medical imaging. GANs consist of two neural networks, the Generator and the Discriminator, competing in a sophisticated ‘cat and mouse’ game, enhancing machine learning and prompting ethical discussions about their use. As GANs evolve, they promise to further revolutionize technology and society.
Guess What? Picking Data Plans Just Got a Whole Lot Easier!
Introduction Recently, I returned to Nigeria after a considerable time in Ghana. While settling back in, I encountered a mundane yet surprisingly challenging task: choosing the best value data plan. …
Adventures in GIS Programming: Techniques for Correcting Geospatial Data from Low-End Devices
Do you work with Geospatial data? The trouble with noisy data points is real. Explore techniques for correction of noisy Geospatial data derived from low-end GPS devices without control inputs