marktechpost

How to Build an Autonomous Machine Learning Research Loop in Google Colab Using Andrej Karpathy’s AutoResearch Framework for Hyperparameter Discovery and Experiment Tracking

In this tutorial, we implement a Colab-ready version of the AutoResearch framework originally proposed by Andrej Karpathy. We build an automated experimentation pipeline that clones the AutoResearch ...
Frontiers

Construction of a clinical prediction model for osteoporosis in asymptomatic elderly population based on machine learning algorithm

Osteoporosis is a metabolic bone disease characterized by a decrease in the amount of bone per unit volume. It is highly prevalent and has a harsh impact on patients' lives. The development of ...
Frontiers

Postpartum depression risk prediction using explainable machine learning algorithms

Postpartum depression (PPD) is a common and serious mental health complication after childbirth, with potential negative consequences for both the mother and her infant. This study aimed to develop an ...
IEEE

Efficient Multidimensional Parameter Estimation Using Machine Learning-Assisted SAGE Algorithm

Abstract: Multidimensional parameter estimation is a critical challenge in fields such as radar, sonar, and wireless communications, where the space-alternating generalized expectation-maximization ...
Phys.org

Spin as an input parameter: Machine learning predicts magnetic properties of materials

Magnetic materials are in high demand. They're essential to the energy storage innovations on which electrification depends and to the robotics systems powering automation. They're also inside more ...
Scientific Research Publishing

A Comparative Study of Ensemble Learning Techniques and Classification Models to Identify Phishing Websites ()

The advent of the internet, as we all know, has brought about a significant change in human interaction and business operations around the world; yet, this evolution has also been marked by security ...
Scientific Research Publishing

Naidu, G., Zuva, T. and Sibanda, E.M. (2023) A Review of Evaluation Metrics in Machine Learning Algorithms. In: Silhavy, R. and Silhavy, P., Eds., Artificial Intelligence ...

ABSTRACT: The advent of the internet, as we all know, has brought about a significant change in human interaction and business operations around the world; yet, this evolution has also been marked by ...
The American Journal of Managed Care

Machine Learning Capable of Predicting Hyperlipidemia in People With HIV

Machine learning models, particularly LightGBM, effectively predict hyperlipidemia in PLWH on HAART for six months, with high accuracy and area under curve values. The study's limitations include ...
IEEE

Improvement of Classification Accuracy in Machine Learning Algorithm by Hyper-Parameter Optimization

Abstract: The manual optimization of hyperparameters is a straightforward and well-known approach, but it is not scalable, particularly when there are several settings and options. In nearly every ...