Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...

This week, Google introduced a new capability for its Gemini 3 Flash model called “Agentic Vision” that fundamentally changes ...

New research from the University of St Andrews, the University of Copenhagen and Drexel University has developed AI computational models that predict the degeneration of neural networks in amyotrophic ...

As a result, the on-chip learning-based neuromorphic system achieved up to 20,000 times faster processing speed while maintaining similar interpretation accuracy to existing conventional techniques.

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 ...

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 ...

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 ...

Python libraries are pre-written collections of code designed to simplify programming by providing ready-made functions for specific tasks. They eliminate the need to write repetitive code and cover ...

This repository contains my implementation of a feed-forward neural network classifier in Python and Keras, trained on the Fashion-MNIST dataset. It closely follows the tutorial by The Clever ...

Background: Accurate differentiation of parkinsonian syndromes remains challenging due to overlapping clinical manifestations and subtle neuroimaging variations. This study introduces an explainable ...