Learn how to build a fully connected, feedforward deep neural network from scratch in Python! This tutorial covers the theory, forward propagation, backpropagation, and coding step by step for a hands ...

Abstract: Algorithmic stock trading has improved tremendously, with Reinforcement Learning (RL) algorithms being more adaptable than classic approaches like mean reversion and momentum. However, ...

Abstract: This paper addresses the critical challenge of enhancing resiliency in smart power grids against cyber-physical disturbances, including cyber-attacks, system faults, and dynamic load ...

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

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 ...

When a blog post by Andrej Karpathy lands in your feed, you pay close attention, simply because few voices in the field of artificial intelligence carry as much conceptual weight. For those who don’t ...

AI agents are reshaping software development, from writing code to carrying out complex instructions. Yet LLM-based agents are prone to errors and often perform poorly on complicated, multi-step tasks ...