Advances in artificial intelligence for porous materials design could impact a wide variety of fields, from orthopedic implants to next-generation batteries.

OpenAI’s new open-weight models are gpt-oss-120b and gpt-oss-20b. The smaller model, gpt-oss-20b, can be run on a consumer ...

Implement Neural Network in Python from Scratch ! In this video, we will implement MultClass Classification with Softmax by making a Neural Network in Python from Scratch. We will not use any build in ...

Gpt-oss-120b can reportedly run on an 80 GB GPU, and OpenAI reports it offers similar performance to its o4-mini model. This ...

Create a fully connected feedforward neural network from the ground up with Python — unlock the power of deep learning!

Classification with Neural Networks Overview This repository contains my implementation of a feed-forward neural network classifier in Python and Keras, trained on the Fashion-MNIST dataset.

The series is designed as an accessible introduction for individuals with minimal programming background who wish to develop practical skills in implementing neural networks from first principles and ...

A graph neural network using data from the Multicenter Epilepsy Lesion Detection (MELD) Project (MELD Graph) can detect epileptogenic focal cortical dysplasia (FCD) on magnetic resonance imaging ...

Fine-Tuning on Experimental Data Our objective with the experimental data set was to fine-tune the predictions of tautomer pairs in aqueous solution using MMFF94-optimized geometries within our ...

Installing Python and related applications on a system without a network connection isn’t easy, but you can do it. Here’s how.

The program evaluated Trojan threats to deep neural networks, examples of which include large language processing, computer vision and reinforcement learning models.