10 things I learned from burning myself out with AI coding agents

Like all AI models based on the Transformer architecture, the large language models (LLMs) that underpin today’s coding ...
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 ...
Hosted on MSN

Build a deep neural network from scratch in Python

We will create a Deep Neural Network python from scratch. We are not going to use Tensorflow or any built-in model to write the code, but it's entirely from scratch in python. We will code Deep Neural ...
IEEE

Convolutional Neural Networks for Direction of Arrival Estimation Compared to Classical Estimators and Bounds

Abstract: Recently, there has been a proliferation of applied machine learning (ML) research, including the use of convolutional neural networks (CNNs) for direction of arrival (DoA) estimation. With ...
IEEE

LSTA-CNN: A Lightweight Spatiotemporal Attention-Based Convolutional Neural Network for ASD Diagnosis Using EEG

Abstract: Electroencephalography (EEG) is an effective assessment tool to identify autism spectrum disorders with low cost, and deep learning has been applied in EEG analysis for extracting meaningful ...