Browsing: Machine

Voyage performance varies even between seemingly identical ships, and models built on vessel-type averages often miss the mark. Manta Marine Technologies (Manta) closes that gap with machine learning (ML) models trained on each vessel’s own operational history. In this post, we show how Manta delivers vessel-specific voyage optimization with machine learning on Amazon Web Services…

If you have used scikit-learn for a while, you have probably written this pipeline. Numeric columns get imputed and scaled. Everything else gets imputed and one-hot encoded. Columns are routed by dtype, so it works on almost any table without you looking at it.

Fitzroy Minerals Inc. (FTZ:TSX.V; FTZFF:OTCQX; C3Y:FSE) identified nine previously untested copper exploration targets using machine learning and 3D seismic imaging at its Buen Retiro project in Chile, where a 5,000-meter drilling program is underway.

Fitzroy Minerals’ machine learning study with Fleet ranks 9 untested copper targets at Buen Retiro, Chile, ahead of a 5,000-meter drill program.

Siddhartha Das explains how machine learning helps his group sift through roughly a trillion simulation data points. It reveals water and electroosmotic flow behavior and could speed the design of sensor-like channels.

MACHINE learning models using routinely available clinical and cognitive data demonstrated moderate-to-good performance in classifying Alzheimer’s disease and cognitive impairment, with accuracy reaching 88.1% across three clinically relevant classification tasks.

Facilitating enhanced 3D visualization of skeletal anatomy, the BoneEnhance machine learning module reportedly provides automated segmentation of bone and surrounding tissues for the Accuro XV ultrasound system.

This is a story about how I spent 21 months building a trading system, wrote down what it would take for it to become a company, and then had two AI models tell me that it hadn’t.

University of Missouri researchers developed an AI tool named MeLSI to analyze gut microbiome data.

Getting information about tomorrow’s weather can be as easy as tapping an application on your smartphone. Modeling weather patterns years down the line is the job of climate scientists. But what about predicting 2-6 weeks out? These intermediate periods, known as subseasons, are when predictive models are critical.