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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 ...
Hosted on MSN

20 Activation Functions in Python for Deep Neural Networks – ELU, ReLU, Leaky-ReLU, Sigmoid, Cosine

Explore 20 different activation functions for deep neural networks, with Python examples including ELU, ReLU, Leaky-ReLU, Sigmoid, and more. #ActivationFunctions #DeepLearning #Python As shutdown ...
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 ...
Invezz

Top crypto price predictions: Pepe Coin, Stellar XLM, Zebec Network

Pepe Coin price has rebounded after forming a falling wedge pattern. Zebec Network token surged after the company was invited to talk in UK parliament. Stellar Lumens (XLM) token price has surged as ...
C&EN

RTK_RAG: Leveraging Retrieval Augmented Generation with Multi-Window Convolutional Neural Networks for Superior ATP Binding Site Prediction in Receptor Tyrosine Kinases

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Receptor tyrosine kinases (RTKs) are key regulators of cellular signaling and are ...
IEEE

Gated-LNN: Gated Liquid Neural Networks for Accurate Water Quality Index Prediction and Classification

Abstract: Surface water quality is of utmost significance to ensure public health and facilitate sustainable economic development. Traditional water quality assessment methods are typically ...
SciELO

Prediction of Microstructural and Mechanical Properties of Steel Welds with Artificial Neural Networks

In the field of materials science, the application of machine learning, particularly neural networks inspired by the human brain, has gained significant traction in recent years. One of the key ...
IEEE

An Effective Neural Network for Communication Signal Prediction via Propagation Path Serialized Representation

Abstract: Communication signal prediction holds great significance for the optimization and deployment of B5G networks. In this letter, we propose a neural network model with Propagation Path ...
Scientific Research Publishing

Occupational Diseases Risk Prediction by Neural Networks ()

This study explores the use of neural networks for occupational disease risk prediction based on worker and workplace characteristics. The goal is to develop a tool to assist occupational physicians ...