Analytics Insight

Best Deep Learning Books to Read in 2026

Overview: Master deep learning with these 10 essential books blending math, code, and real-world AI applications for lasting ...
GitHub

City2Graph: GeoAI with Graph Neural Networks (GNNs) and Spatial Network Analysis

This installs the core functionality without PyTorch and PyTorch Geometric. To use PyTorch and PyTorch Geometric with City2Graph installed from conda-forge, you need to manually add these libraries to ...
Deep Learning with Yacine on MSN

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

EncodingNet: A Novel Encoding-Based MAC Design for Efficient Neural Network Acceleration

Abstract: Deep neural networks (DNNs) have achieved great breakthroughs in many fields such as image classification and natural language processing. However, the execution of DNNs needs to conduct ...
Deep Learning with Yacine on MSN

Create a perceptron from scratch in Python – step by step tutorial

Learn how to build a perceptron from scratch in Python! This tutorial covers the theory, coding, and practical examples, helping you understand the foundations of neural networks and machine learning.
TMCnet

Bridging Silence: A Real-Time Sign Language to English Text Translation System Using Python, OpenCV, and Convolutional Neural Networks

Bridging communication gaps between hearing and hearing-impaired individuals is an important challenge in assistive technology and inclusive education. In an attempt to close that gap, I developed a ...
IEEE

HGNN-GAMS: Heterogeneous Graph Neural Networks for Graph Attribute Mining and Semantic Fusion

Abstract: Heterogeneous Graph Neural Networks (HGNNs) have attracted significant research attention in recent years due to their ability to capture complex interactions among various node types in ...