weaksupervision

The traditional paradigm of supervised machine learning relies heavily on large volumes of accurately labeled training data. However, acquiring such high-quality labeled datasets often proves prohibitively expensive, time-consuming, or simply impractical in many real-world scenarios. This challenge has given rise to weak supervision techniques in machine learning, a revolutionary approach that enables models to learn … Read more