Frontiers

Neural Network Dynamics: Unraveling Spiking and Synaptic Plasticity in Learning and Memory

Neuroscience continually strives to unravel the intricate relationship between neural network morphology, spiking dynamics, and their resulting functional ...
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 ...

Biology-inspired brain model matches animal learning and reveals overlooked neuron activity

A new computational model of the brain based closely on its biology and physiology has not only learned a simple visual ...

Researchers make “neuromorphic” artificial skin for robots

The researchers behind the recent work, based in China, decided to implement something similar for an artificial skin that ...
Learn With Jay 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 Llama series of models from Meta

Meta’s most popular LLM series is Llama. Llama stands for Large Language Model Meta AI. They are open-source models. Llama 3 was trained with fifteen trillion tokens. It has a context window size of ...
Analytics Insight

What are the Best Python Libraries for Reinforcement Learning in 2025?

Overview:  Reinforcement learning in 2025 is more practical than ever, with Python libraries evolving to support real-world simulations, robotics, and deci ...
Learn With Jay on MSN

Python neural network for multiclass classification using softmax

Implement Neural Network in Python from Scratch ! In this video, we will implement MultClass Classification with Softmax by ...
IEEE

Survey on Graph Neural Networks

Graph Neural Networks (GNNs) have become a powerful tool in order to learn from graph-structured data. Their ability to capture complex relationships and dependencies within graph structures, allows ...
IEEE

Design of Hierarchical Neural Networks Using Deep LSTM and Self-Organizing Dynamical Fuzzy-Neural Network Architecture

Abstract: Time series forecasting is an essential and challenging task, especially for large-scale time-series (LSTS) forecasting, which plays a crucial role in many real-world applications. Due to ...