This project demonstrates the use of regularization techniques—Lasso and Ridge—to improve model performance by reducing overfitting and stabilizing predictions. Regularization helps control model ...

1 School of Computing and Data Science, Wentworth Institute of Technology, Boston, USA. 2 Department of Computer Science and Quantitative Methods, Austin Peay State University, Clarksville, USA. 3 ...

After spending some solid time riding the Ausom L2 Max Dual Motor, what stuck with me most wasn't just the speed or power—it was how easy it felt to get used to. From the first ride, it gave off a ...

What if you could create your very own personal AI assistant—one that could research, analyze, and even interact with tools—all from scratch? It might sound like a task reserved for seasoned ...

This video is an overall package to understand L2 Regularization Neural Network and then implement it in Python from scratch. L2 Regularization neural network it a technique to overcome overfitting.

While child-sized humanoid robots like the Unitree R1 have come down in price, not everybody has a spare $6,000 to throw around to play with robots, and smaller models like the Tonybot are more ...

Abstract: Several studies have used convolutional neural networks and long short-term memory (CNN-LSTM) models to detect phishing emails because of their ability to capture attack patterns from raw ...

Abstract: In this work, we propose a high-order regularization method to solve the ill-conditioned problems in robot localization. Numerical solutions to robot localization problems are often unstable ...