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 ...

A CNN data reporter highlighted the Democratic Party's historic divisions and basement-level approval ratings as members search for new direction after election defeat.

CUDA Neural Network for MNIST Classification A high-performance neural network implementation using CUDA and cuBLAS for MNIST digit classification. This project demonstrates GPU-accelerated deep ...

A new study led by researchers from the Yunnan Observatories of the Chinese Academy of Sciences has developed a neural network-based method for large-scale celestial object classification ...

For decades, scientists have looked to light as a way to speed up computing. Photonic neural networks—systems that use light instead of electricity to process information—promise faster speeds ...

Additionally, using foundation model encoders directly without fine-tuning resulted in generally poor performance on the classification task. Conclusion: Our findings suggest that deep learning models ...

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 ...

The recognition of handwritten digits has been among the most enduring fundamental problems explored in the field of machine learning and computer vision. The objective of this work is to design a ...

However, a relatively new form of quantile regression is neural network quantile regression -- a variation of neural network regression. By using a custom loss function that penalizes low predictions ...