[G-Certification Day 8] What is Supervised Learning in AI? Linear Regression, SVM, and Decision Trees

Hello everyone, stay safe!! This is Takachan the engineer.AI that identifies spam, AI that predicts sales, AI that ...
Tech Times on MSN

NVIDIA Kumo relational beats XGBoost on enterprise databases without feature engineering

Relational foundation model NVIDIA Kumo Relational beats XGBoost and AutoGluon across 41 benchmark tasks on enterprise ...
BIOENGINEER

Machine learning predicts HIV patients at risk of dropping out of antiretroviral care

Random Forest and XGBoost models predicted loss to follow-up among ART patients in Zimbabwe with high internal accuracy, ...
BIOENGINEER

Machine learning steers biomass carbon cathodes to stronger zinc-ion supercapacitors

A machine learning model built on eight material descriptors predicted the specific capacity of nitrogen-doped porous carbon ...
TodoMountainBike

An AI Model Got Nearly 80% of Bicycle Crashes Right. It Failed to Identify Every Severe One

A Texas study of 2,394 child bicycle crashes reveals why an AI model with nearly 80% accuracy failed to identify any fatal or ...

[G Certification Day 9] What is Unsupervised Learning in AI? k-means, Principal Component Analysis, and Recommendation Systems

Hello everyone, stay safe!! This is Takachan the engineer.AI that identifies spam, AI that predicts sales, AI that ...
Rebellion Research

How to Predict Market Regimes with AI for Long-Short Strategy

See how predicting market regimes with AI uses clustering and probability signals to guide long-short positioning, sizing, ...
HackerNoon

HackerNoon - Investigating Feature Leakage and Proxy Variables in a Clash of Clans ML Model

Can a predictive feature look like data leakage? A Clash of Clans ML case study on proxies, feature audits, domain knowledge, ...
NewsMobile

AI Model Predicts Diabetes Risk in Fatty Liver Patients With 89% Accuracy

Researchers have developed an artificial intelligence model that could help identify patients with non-alcoholic fatty liver ...
GitHub

Intelligent Systems for Thyroid Disease Detection Using Machine Learning

This project uses Machine Learning algorithms to detect and classify thyroid conditions based on clinical and laboratory test results. It aims to support thyroid disease analysis by identifying ...
The Transmitter

Examining the bridge between neuroscience and AI

A citation analysis reveals that the connection between the two fields is real and gaining momentum. But we need to find ways ...