particularly using ML (Machine Learning) approaches. For a paper to be included in our analysis, it had to employ an ML-based approach to identify deception, utilize datasets, and be written in ...

This process involves dividing data into subsets for training, validating, and testing machine learning models. It helps ...

But these AI and machine learning datasets — like the humans that designed them — aren’t without their flaws. Studies show that biases and mistakes color many of the libraries used to train ...

Yahoo announced this morning that it’s making the largest-ever machine learning dataset available to the academic research community through its ongoing program, Yahoo Labs Webscope. The new ...

With machine learning on the uptick we've done the leg work for you and assembled a list of top public domain datasets as ranked by Github. The full list, along with several other lists of ...

Meta AI has released LeanUniverse, an open source machine learning (ML) library designed to address the growing challenges of managing datasets in large-scale machine learning projects. Built on the ...

Rice University computer science researchers have found bias in widely used machine learning tools used for immunotherapy research. Ph.D. students Anja Conev, Romanos Fasoulis and Sarah Hall-Swan ...

Deep learning automation startup Deci AI Ltd. today announced the launch of a free and open-source artificial intelligence tool that can profile datasets for model training purposes.. The company ...

An influential machine learning dataset—the likes of which has been used to train numerous popular image-generation applications—includes thousands of suspected images of child sexual abuse, a ...