Morning Overview on MSN

Scientists grew mini brains and trained them to crack an engineering problem

Researchers at the University of California, Santa Cruz have trained lab-grown brain organoids to solve a goal-directed task, ...

Machine learning helps solve a central problem of quantum chemistry

By applying new methods of machine learning to quantum chemistry research, Heidelberg University scientists have made significant strides in computational chemistry. They have achieved a major ...

Machine learning algorithm fully reconstructs LHC particle collisions

The CMS Collaboration has shown, for the first time, that machine learning can be used to fully reconstruct particle ...
The Lancet

When to and when not to use machine learning in risk prediction models

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...
North Penn Now

Machine Learning Using Python: A Complete Learning Path With Practical Projects

Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...
VentureBeat

Google’s ‘Nested Learning’ paradigm could solve AI's memory and continual learning problem

Researchers at Google have developed a new AI paradigm aimed at solving one of the biggest limitations in today’s large language models: their inability to learn or update their knowledge after ...
Scientific Research Publishing

Amin, F. and Mahmoud, M. (2022) Confusion Matrix in Binary Classification Problems: A Step-by-Step Tutorial. Journal of Engineering Research, 6, Article No. 1.

ABSTRACT: Accurate prediction of malaria incidence is indispensable in helping policy makers and decision makers intervene before the onset of an outbreak and potentially save lives. Various ...
GitHub

basic-binary-classification-problem

This repository contains two basic prediction models: Credit Card Fraud Detection and Titanic Survival Prediction. Both models demonstrate the use of machine learning for binary classification tasks.
BMJ

Prediction of zero-dose children using supervised machine learning algorithm in Tanzania: evidence from the recent 2022 Tanzania Demographic and Health Survey

Objectives This study aimed to employ machine learning algorithms to predict the factors contributing to zero-dose children in Tanzania, using the most recent nationally representative data. Design ...
Scientific Research Publishing

Credit Score Classification Using Advanced Machine Learning: A Comprehensive Approach ()

1 Department of Computer Science, Rutgers University, New Brunswick, NJ, USA. 2 Department of Computer Science, Rochester Institute of Technology, Rochester, NY, USA. This paper presents a ...
IEEE

An Overview and Classification of Machine Learning Approaches for Radar Signal Deinterleaving

Abstract: Electronic Warfare (EW) receivers are passive systems that are designed to detect and identify active radar emitters in the environment. The radar pulses emitted by multiple sources are ...