The Data Science Lab Binary Classification Using PyTorch: Preparing Data Dr. James McCaffrey of Microsoft Research kicks off a series of four articles that present a complete end-to-end ...

Training machine learning models for computer vision use cases takes massive amounts of images. Often, those images are mislabeled, broken or duplicated, leading to sub-par model performance. But with ...

“About 90 percent of the information people consume is visual,” said John Dony, director of the Campbell Institute. “Taking in that much visual data can lead us to have inattentional blindness – only ...

Generating synthetic data is useful when you have imbalanced training data for a particular class, for example, generating synthetic females in a dataset of employees that has many males but few ...

Purpose: Is used to train the machine learning model. Function: Think of it as the study material for the model. It provides examples and patterns for the model to learn from and build its internal ...

While artificial intelligence (AI) systems, such as home assistants, search engines or large language models like ChatGPT, may seem nearly omniscient, their outputs are only as good as the data on ...