Deep learning model enables accurate and scalable drug-drug interaction prediction

Managing complex medical conditions often requires the simultaneous use of multiple different drugs, referred to as polypharmacy. While necessary, this significantly increases the risk of drug-drug ...
Analytics Insight

Explore Data Science This Weekend: Best YouTube Channels to Follow

Overview: Free YouTube channels provide structured playlists covering AI, ML, and analytics fundamentals.Practical coding demonstrations help build real-world d ...
Frontiers

AI-Driven Complex Networks: Structure, Dynamics, and Intelligent Applications

In an increasingly interconnected world, understanding the behavior and structure of complex networks has become essential across disciplines. These ...
GitHub

Neural Network from Scratch

Eric Gutiérrez, 6th February 2026. A Python implementation of a 1-hidden layer neural network built entirely from first principles. This project avoids deep learning libraries (like TensorFlow or ...
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 ...
Beebom

What is CNN in Deep Learning? The AI Behind Computer Vision

CNN in deep learning is a special type of neural network that can understand images and visual information. It works just like human vision: first it detects edges, lines and then recognizes faces and ...
IEEE

Deep Operator Neural Network Model Predictive Control

Abstract: In this paper, we consider the design of model predictive control (MPC) algorithms based on deep operator neural networks (DeepONets) (Lu et al. 2021). These neural networks are capable of ...
Frontiers

An AI methodology to reduce training intensity, error rates, and size of neural networks

Massive computing systems are required to train neural networks. The prodigious amount of consumed energy makes the creation of AI applications significant polluters ...
Hosted 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 ...
GitHub

STM-Graph: A Python Framework for Spatio-Temporal Mapping and Graph Neural Network Predictions

STM-Graph is a Python framework for analyzing spatial-temporal urban data and doing predictions using Graph Neural Networks. It provides a complete end-to-end pipeline from raw event data to trained ...
IEEE

Wormhole Dynamics in Deep Neural Networks

Abstract: This work investigates the generalization behavior of deep neural networks (DNNs), focusing on the phenomenon of “fooling examples,” where DNNs confidently classify inputs that appear random ...