TechAnnouncer

Demystifying Machine Languages: Practical Examples and Core Concepts

Machine learning can sound pretty complicated, right? Like something only super-smart tech people get. But honestly, it’s ...
IEEE

An Adaptive Robust Support Vector Machine with Sequential Minimal Optimization for Imbalanced Data Classification

Abstract: Class imbalanced classification presents a considerable difficulty in machine learning, as conventional algorithms typically exhibit bias towards the majority class, compromising minority ...
International Monetary Fund

GDP Nowcasting Performance of Traditional Econometric Models vs Machine-Learning Algorithms: Simulation and Case Studies

Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in ...
Hosted on MSN

Uber and DoorDash now disclose when algorithms set prices. There's still one big question.

New Yorkers got a little more visibility this week into when apps like Uber and DoorDash use algorithms to set prices. The state's Algorithmic Pricing Disclosure Act took effect on Monday. Under the ...
TheServerSide

Google Machine Learning Certification Sample Questions

Community driven content discussing all aspects of software development from DevOps to design patterns. The Google Cloud Professional Machine Learning Engineer certification validates your ability to ...
TheServerSide

Sample Questions for AWS' Machine Learning Associate Certification

Community driven content discussing all aspects of software development from DevOps to design patterns. The AWS Machine Learning Associate certification validates your ability to configure, build, and ...
IEEE

A Fuzzy Granular Support Vector Machine for Network Traffic Anomaly Detection

Abstract: To address the challenges in network anomaly detection, such as data label imbalance and the poor performance of traditional Support Vector Machines (SVM) in fitting high-dimensional, ...
Frontiers

Support vector machine-based classification of bulimia nervosa using diffusion tensor imaging

Alterations in brain structure have been suggested to be associated with bulimia nervosa (BN). This study aimed to employ machine learning (ML) methods based on diffusion tensor imaging (DTI) to ...
ascopubs.org

Development of a Machine Learning Model for Aspyre Lung Blood: A New Assay for Rapid Detection of Actionable Variants From Plasma in Patients With Non–Small Cell Lung Cancer

Development and Validation of an Ipsilateral Breast Tumor Recurrence Risk Estimation Tool Incorporating Real-World Data and Evidence From Meta-Analyses: A Retrospective Multicenter Cohort Study Data ...
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 ...