来自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 making a Neural Network in Python from Scratch. We will not use any build in ...
来自MSN

Dropout In Neural Networks — Prevent Overfitting Like A Pro (With Python)

This video is an overall package to understand Dropout in Neural Network and then implement it in Python from scratch. Dropout in Neural Network is a regularization technique in Deep Learning to ...
C&EN

NeuralTSNE: A Python Package for the Dimensionality Reduction of Molecular Dynamics Data ...

Institute of Physics, Faculty of Physics, Astronomy and Informatics, Nicolaus Copernicus University, Grudziądzka 5, 87-100 Toruń, Poland ...
Frontiers

Quantized convolutional neural networks: a hardware perspective

With the rapid development of machine learning, Deep Neural Network (DNN) exhibits superior performance in solving complex problems like computer vision and natural language processing compared with ...
GitHub

OyewoleRasheed/Classification-with-Neural-Networks-using-Python

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 ...
gc.cuny

Programming Neural Networks in Python: Part II

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 ...
gc.cuny

Programming Neural Networks in Python: a multi-part workshop

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 ...
IEEE

Bayesian Neural Networks via MCMC: A Python-Based Tutorial

Abstract: Bayesian inference provides a methodology for parameter estimation and uncertainty quantification in machine learning and deep learning methods. Variational inference and Markov Chain ...
IEEE

Tutorial: Artificial Neural Networks for Discrete-Event Simulation

Abstract: This advanced tutorial explores some recent applications of artificial neural networks (ANNs) to stochastic discrete-event simulation (DES). We first review some basic concepts and then give ...