Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...

The IT team at North-Eastern Hill University has launched an innovative AI-driven landslide mapping tool specifically for Meghalaya. Utilizing an impressive combination of ten machine learning ...

Accurately tracking atmospheric greenhouse gases requires not only fast predictions but also reliable estimates of ...

This paper presents a novel framework for optimizing Carbon Release (CR) through an AI-driven approach to Fossil Fuel Intake (FFI) management. We propose a new training methodology for AI models to ...

The Department of Information Technology at North-Eastern Hill University has developed a Landslide Susceptibility Map using ...

Approximately 7% of the state falls under the “very high-risk” category, while 6% is classified as “high risk.” East Khasi Hills emerged as the most vulnerable district, with nearly 730 square ...

For example, a Convolutional Neural Network (CNN) trained on thousands of radar echoes can recognize the unique spatial signature of a small metallic fragment, even when its signal is partially masked ...

Researchers have developed a powerful machine learning framework that can accurately predict and optimize biochar production from algae, offering a ...

We independently review everything we recommend. When you buy through our links, we may earn a commission. Learn more› By Justin Pot Our upgrade pick, Babbel, has discontinued its premium Live service ...

Biocomputing research is testing living neurons for computation as scientists look for energy-efficient alternatives to ...

LinkedIn’s head of engineering for talent solutions explains how fine-tuned LLMs and agentic AI architectures are replacing ...

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