Deep Learning with Yacine on MSN

Deep neural network from scratch in Python – fully connected feedforward tutorial

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 ...

AnchorChartPRO Launches All-in-One Visual Content Platform

AnchorChartPRO’s All-in-One EdTech Solution Now Live Columbus, United States – January 1, 2026 / AnchorChartPRO / AnchorChartPRO, an innovative education technology startup headquartered in Columbus, ...
Analytics Insight

What are the Best Python Libraries for Reinforcement Learning in 2025?

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

How We Learn Step-Level Rewards from Preferences to Solve Sparse-Reward Environments Using Online Process Reward Learning

In this tutorial, we explore Online Process Reward Learning (OPRL) and demonstrate how we can learn dense, step-level reward signals from trajectory preferences to solve sparse-reward reinforcement ...
IEEE

Deep Reinforcement Learning for Distribution System Operations: A Tutorial and Survey

The rapid evolution of modern electric power distribution systems into complex networks of interconnected active devices, distributed generation (DG), and storage poses increasing difficulties for ...
eLife

Online reinforcement learning of state representation in recurrent network supported by the power of random feedback and biological constraints

In this important study, the authors model reinforcement-learning experiments using a recurrent neural network. The work examines if the detailed credit assignment necessary for back-propagation ...
Scientific Research Publishing

Hussain, F., Hassan, S.A., Hussain, R. and Hossain, E. (2020) Machine Learning for Resource Management in Cellular and IoT Networks: Potentials, Current Solutions, and Open ...

ABSTRACT: As cloud computing continues to evolve, managing CPU resources effectively has become a critical task for ensuring system performance and efficiency. Traditional CPU resource management ...
Scientific Research Publishing

Xu, T., et al. (2024) Reinforcement Learning for Adaptive Intrusion Detection: Balancing Performance and False Positives. IEEE Transactions on Neural Networks and Learning ...

ABSTRACT: Cybersecurity has emerged as a global concern, amplified by the rapid expansion of IoT devices and the growing digitization of systems. In this context, traditional security solutions such ...
IEEE

Enhancing Deep Reinforcement Learning: A Tutorial on Generative Diffusion Models in Network Optimization

Abstract: Generative Diffusion Models (GDMs) have emerged as a transformative force in the realm of Generative Artificial Intelligence (GenAI), demonstrating their versatility and efficacy across ...
Phys.org

Self-learning neural network cracks iconic black holes

A team of astronomers led by Michael Janssen (Radboud University, The Netherlands) has trained a neural network with millions of synthetic black hole data sets. Based on the network and data from the ...
Forbes

The Rise And Rise Of Reinforcement Learning: AI’s Quiet Revolution

Forbes contributors publish independent expert analyses and insights. Author, Researcher and Speaker on Technology and Business Innovation. Apr 19, 2025, 03:24am EDT Apr 21, 2025, 10:40am EDT ...