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Backpropagation from scratch in Python – step by step neural network tutorial

Learn how backpropagation works by building it from scratch in Python! This tutorial explains the math, logic, and coding behind training a neural network, helping you truly understand how deep ...
IEEE

TriadMapper: A Necessity–Diversity–Sensitivity Aware Network for Building Vector Mapping

Abstract: Building vectorization from remote sensing imagery is a critical task challenged by three persistent issues: distinguishing buildings from complex surroundings, adapting to vast scale ...
GitHub

Factor Augmented Network Informed Restricted Vector Autoregression

├── LICENSE <- Open-source license if one is chosen ├── Makefile <- Makefile with convenience commands like `make data` or `make train` ├── README.md <- The top-level README for developers using this ...
IEEE

Model-Free Predictive Control of IPMSM with Adaptive Voltage Vector Coefficient Based on a Predictor-Based Neural Network

Abstract: In model predictive control (MPC), the voltage vector coefficient in the predictive model is closely linked to the model parameters, significantly affecting control performance. However, ...
GitHub

Generative AI for Beginners: Project-Based Guide to Building RAG Agents

A comprehensive, beginner-friendly, project-driven curriculum on Generative AI and Retrieval-Augmented Generation (RAG) Agents. Learn core concepts like prompt engineering, vector embeddings, chain ...