TDAN.com

Using Artificial Intelligence and Machine learning to Improve Data Quality in Cloud Native Data Pipelines

Introduction: Why Data Quality Is Harder Than Ever Data quality has always been important, but in today’s world of ...
Opinion
Learn With Jay on MSNOpinion

Supervised learning made easy: Real-world example explained

In this video, we will study Supervised Learning with Examples. We will also look at types of Supervised Learning and its applications. Supervised learning is a type of Machine Learning which learns ...
IEEE

Machine Learning Techniques to Improve the Cognitive Workload Classification Using Multimodal Sensors’ Data

Abstract: Using machine learning applied to multimodal physiological data allows the classification of cognitive workload (low, moderate, or high load) during task performance. However, current ...
SciELO

Obesity classification: a comparative study of machine learning models excluding weight and height data

OBJECTIVE: Obesity is a global health problem. The aim is to analyze the effectiveness of machine learning models in predicting obesity classes and to determine which model performs best in obesity ...
Law

Training Alone Is Not Enough: Lessons From 'Recentive' and USPTO AI Examples on Patent Eligible Machine-Learning Claims

The Recentive decision exemplifies the Federal Circuit’s skepticism toward claims that dress up longstanding business problems in machine-learning garb, while the USPTO’s examples confirm that ...
Hosted on MSN

Logistic Regression Machine Learning Example ¦ Simply Explained

Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable can only take binary values. Some real world examples where Logistic ...
Frontiers

Migraine triggers, phases, and classification using machine learning models

1 San Juan Bautista School of Medicine, Caguas, Puerto Rico, United States 2 Independent Researcher, Monmouth County, NJ, United States Background: In many countries, patients with headache disorders ...
Scientific Research Publishing

Belkin, M., Niyogi, P. and Sindhwani, V. (2006) Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples. Journal of Machine Learning ...

ABSTRACT: The stochastic configuration network (SCN) is an incremental neural network with fast convergence, efficient learning and strong generalization ability, and is widely used in fields such as ...
Forbes

How AI, Data Science, And Machine Learning Are Shaping The Future

Forbes contributors publish independent expert analyses and insights. Writes about the future of finance and technology, follow for more. We live in a world where machines can understand speech, ...
Frontiers

Improved cattle farm classification: leveraging machine learning and linked national datasets

While many countries have registries of livestock farms, it can be challenging to obtain information on their primary production type. For example, for Swiss farms registered as keeping cattle, a ...