Hosted on MSN

Digit Recognition With Deep Learning — PyTorch Beginner Project

Learn how to build a digit recognition model from scratch using PyTorch! This beginner-friendly deep learning project walks you through loading the MNIST dataset, creating a neural network, training ...
IEEE

Optimizing Federated Learning on Non-IID Data with Reinforcement Learning

Abstract: The widespread deployment of machine learning applications in ubiquitous environments has sparked interests in exploiting the vast amount of data stored on mobile devices. To preserve data ...
Frontiers

ALBSNN: ultra-low latency adaptive local binary spiking neural network with accuracy loss estimator

Spiking neural network (SNN) is a brain-inspired model with more spatio-temporal information processing capacity and computational energy efficiency. However, with the increasing depth of SNNs, the ...
Visual Studio Magazine

Convolutional Neural Networks for MNIST Data Using PyTorch

Dr. James McCaffrey of Microsoft Research details the "Hello World" of image classification: a convolutional neural network (CNN) applied to the MNIST digits dataset. The "Hello World" of image ...
IEEE

Optimizing Federated Learning on Device Heterogeneity with A Sampling Strategy

Abstract: Federated learning (FL) is a novel machine learning that performs distributed training locally on devices and aggregating the local models into a global one. The limited network bandwidth ...
InfoWorld

14 open source tools to make the most of machine learning

Spam filtering, face recognition, recommendation engines — when you have a large data set on which you’d like to perform predictive analysis or pattern recognition, machine learning is the way to go.