The package implements 86 variants of the Synthetic Minority Oversampling Technique (SMOTE). Besides the implementations, an easy to use model selection framework is supplied to enable the rapid ...

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Machine learning requires humans to manually label features while deep learning automatically learns features directly from raw data. ML uses traditional algorithms like decision tress, SVM, etc., ...

Abstract: The extensive user engagement on YouTube leads to a flood of comments, creating challenges for content creators who aim to understand audience sentiment. Previous studies have mainly ...

Abstract: This study responds to the increasing phenomenon of elsagate content on various platforms, especially on YouTube Kids and YouTube, which are often accessed by children. Elsagate content ...

During the Autumn Term, my Academic Support Hours are 14:00 - 16:00 on Tuesday. I can meet on Zoom by request at these times. (I will check my email during these support hours and respond with a link.

The challenge with TinyML is to extract the maximum performance/efficiency at the lowest footprint for AI workloads on microcontroller-class hardware. The TinyML-CAM ...

We released two large scale datasets for research on learning to rank: MSLR-WEB30k with more than 30,000 queries and a random sampling of it MSLR-WEB10K with 10,000 queries. The datasets are machine ...