This project fine-tunes a BERT model on the AG News dataset for supervised news topic classification using pretrained contextual embeddings. The trained model is deployed as a live AI application for ...

This project fine-tunes a BERT model on the AG News dataset for supervised news topic classification using pretrained contextual embeddings. The trained model is deployed as a live AI application for ...

Abstract: Most text classification models based on traditional machine learning algorithms have problems such as curse of dimensionality and poor performance. In order to solve the above problems, ...

In petroleum geophysics, well logs are fundamental for subsurface characterization; however, missing logs frequently occur due to tool failure, legacy data gaps, or economic constraints, limiting ...

Apple's autocorrect on iPhone and iPad always aims to help when you're typing a message, but it's by no means perfect, and some of the replacements it continually spews out can be frustrating.

Text-based depression estimation using natural language processing has emerged as a feasible approach for early mental health screening. However, most existing reviews often included studies with weak ...

If old sci-fi shows are anything to go by, we're all using our computers wrong. We're still typing with our fingers, like cave people, instead of talking out loud the way the future was supposed to be ...

ABSTRACT: This paper evaluates the performance of multiple machine learning models in predicting NBA game outcomes. Both regression and classification approaches were explored, with models including ...

A large-scale randomized trial of texting therapy concluded that its outcomes were as good as video sessions in treating depression. By Ellen Barry One of the most popular mental health innovations of ...

Since transformer-based language models were introduced in 2017, they have been shown to be extraordinarily effective across a variety of NLP tasks including but not limited to language generation.