Analytics Insight

Machine Learning, Stanford University

Stanford University’s Machine Learning (XCS229) is a 100% online, instructor-led course offered by the Stanford School of ...

FluxMateria Launches Physics-Based Screening Platform. 3.6 Million x Faster Than DFT, No AI

A breakthrough deterministic physics kernel delivers molecular, materials, and reaction screening across three ...
Scientific Research Publishing

Dietterich, T.G. (2000) Ensemble Methods in Machine Learning. In: Kittler, J. and Roli, F., Eds., International Workshop on Multiple Classifier Systems, Springer, 1-15.

ABSTRACT: This paper proposes a hybrid machine learning framework for early diabetes prediction tailored to Sierra Leone, where locally representative datasets are scarce. The framework integrates ...
BMJ

Development of an interpretable machine learning model for frailty risk prediction in older adult care institutions: a mixed-methods, cross-sectional study in China

Objective To develop and validate an interpretable machine learning (ML)-based frailty risk prediction model that combines real-time health data with validated scale assessments for enhanced ...
IEEE

Quo Vadis, Quantum Machine Learning?: Quantum kernel methods meet Earth observation

Abstract: The analysis of satellite images has attracted significant research interest due to its numerous applications and unparalleled scalability in Earth observation (EO). Although artificial ...
usace.army.mil

Army establishes new AI, machine learning career path for officers

WASHINGTON – The U.S. Army has established a new career pathway for officers to specialize in artificial intelligence and machine learning (AI/ML), formally designating the 49B AI/ML Officer as an ...
C&EN

A New Pulsed Neutron-Gamma Density Logging Method Based on Gamma-Ray Spectra and Machine Learning

However, NGD faces several challenges associated with gamma-ray generation and attenuation complexities. Unlike GGD, which utilizes 0.662 MeV monoenergetic γ rays from a 137 Cs source, NGD employs ...
Frontiers

Estimating rice yield-related traits using machine learning models integrating hyperspectral and texture features

Rapidly estimating multiple trait indicators simultaneously, nondestructively, and with high precision is an important means of accurate diagnosis in modern phenomics. Increasing the accuracy of ...
InfoWorld

AI and machine learning outside of Python

In some ways, Java was the key language for machine learning and AI before Python stole its crown. Important pieces of the data science ecosystem, like Apache Spark, started out in the Java universe.
BMJ

Predicting disease progression in people living with HIV using machine learning and a nomogram: a 10-year cohort study based in Xinjiang, China

Objectives Current prediction models for disease progression to AIDS in people living with HIV primarily rely on traditional statistical methods. This study aimed to develop and compare four machine ...
GitHub

Doubly-Robust-Kernel-Proxy-Variable-Algorithm

This repository provides code for a doubly robust algorithm for Proxy Causal Learning (PCL) using kernel methods, avoiding density ratio estimation. All code is written in Python 3 using the JAX ...
GitHub

quantum-kernel-methods

Quoptuna is a Python package supporting over 20 quantum machine learning models using PennyLane. These models include classifiers, neural networks, and kernel-based approaches. Quoptuna integrates ...