By transforming movement into data, Timothy Dunn is reshaping how scientists can study behavior and the brain.

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

Abstract: To tackle the challenge of data diversity in sentiment analysis and improve the accuracy and generalization ability of sentiment analysis, this study first cleans, denoises, and standardizes ...

The use of modern technologies, including Immersive Mixed Reality (IMR) technologies, to present information on climate change has become essential due to their ability to simplify information and ...

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 ...

Researchers at Osaka Metropolitan University have discovered a practical way to detect and fix common labeling errors in large radiographic collections. By automatically verifying body-part, ...

Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. Topics: Face detection with Detectron 2, Time Series anomaly detection with LSTM ...

This paper focuses on the nonlinear correlation between investor sentiment and stock returns and conducts in-depth research with the aid of deep learning and text mining techniques. First of all, sort ...

Traditional bibliometric approaches to research impact assessment have predominantly relied on citation counts, overlooking the qualitative dimensions of how research is received and discussed.

President Trump does not subscribe to the traditional notion of being president for all Americans. By Peter Baker Peter Baker has covered the past six presidencies. He reported from Washington. The ...