We will create a Deep Neural Network python from scratch. We are not going to use Tensorflow or any built-in model to write ...

Overview:  Reinforcement learning in 2025 is more practical than ever, with Python libraries evolving to support real-world simulations, robotics, and deci ...

From disaster zones to underground tunnels, robots are increasingly being sent where humans cannot safely go. But many of ...

Abstract: In this paper, Python programming is employed to study the electromagnetic finite element method (FEM) and Bayesian deep learning. Rectangular cavity and folded waveguide (FWG) slow-wave ...

So far, running LLMs has required a large amount of computing resources, mainly GPUs. Running locally, a simple prompt with a typical LLM takes on an average Mac ...

This is the official repository of the paper "TabM: Advancing Tabular Deep Learning With Parameter-Efficient Ensembling". It consists of two parts: One dot represents a performance score on one ...

Abstract: This research addresses the imperative need for advanced detection mechanisms for the identification of phishing websites. For this purpose, we explore state-of-the-art machine learning, ...