Overview:Practical projects can help you showcase technical skill, programming knowledge, and business awareness during the ...

Abstract: Deep Neural Networks (DNNs) that aim to maximize accuracy and decrease loss can be trained using optimization algorithms. One of the most significant fields of research is the creation of an ...

What if you could turn Excel into a powerhouse for advanced data analysis and automation in just a few clicks? Imagine effortlessly cleaning messy datasets, running complex calculations, or generating ...

This repository contains the technical implementation of the paper Statistical Test-based Adversarial Client Detection in Federated Learning under Poisoning Attacks, as well as proof of its results.

This hands-on tutorial will walk you through the entire process of working with CSV/Excel files and conducting exploratory data analysis (EDA) in Python. We’ll use a realistic e-commerce sales dataset ...

Harvard University announced Thursday it’s releasing a high-quality dataset of nearly 1 million public-domain books that could be used by anyone to train large language models and other AI tools. The ...

This paper presents a new dataset of monetary policy shocks for 21 advanced economies and 8 emerging markets from 2000-2022. We use daily changes in interest rate swap rates around central bank ...

Abstract: In this work, two different deep learning architectures Residual Network (ResNet) and VGG Network are implemented for the MNIST digit recognition challenge. With a changed architecture, the ...

Pew Research Center makes its data available to the public for secondary analysis after a period of time. See this post for more information on how to use our datasets and contact us at ...