Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and data preprocessing. If you''ve ever built a predictive model, worked on a ...

Social media platform X will open its new algorithm to the public in seven days, Elon Musk said on Saturday, including the code used to decide what posts and advertisements are recommended to users.

We use heuristics to solve computationally difficult problems where optimal solutions are too expensive to deploy, hard to manage, or otherwise inefficient. Our prior work, MetaOpt, shows many of the ...

U.S. Rep. April McClain Delaney has introduced a bill that would allow tech companies to be sued if their algorithms negligently expose users to harmful content. Together with Utah Republican Mike ...

The way people discover content, like music and art, is changing fast. AI-powered recommendation algorithms are creating fragmented social media feeds, carving pop culture into tiny, personalized ...

An artificial-intelligence algorithm that discovers its own way to learn achieves state-of-the-art performance, including on some tasks it had never encountered before. Joel Lehman is at Lila Sciences ...

An automated MATLAB application for brain tumor detection and segmentation from MRI images. This project uses image processing and a Support Vector Machine (SVM) classifier to identify and highlight ...

Learn the Adagrad optimization algorithm, how it works, and how to implement it from scratch in Python for machine learning models. #Adagrad #Optimization #Python Trump administration looking to sell ...

This project demonstrates the application of various machine learning algorithms for heart disease classification. By comparing the performance of SVM, MLP, and Random Forest models, we can determine ...

Abstract: To solve the problem of low prediction accuracy of SVM algorithm, this paper proposes a prediction model research method based on PSO-SVM kernel function hybrid algorithm, designs global and ...