Results for tag: "Self Supervised Learning"

Self-supervised learning is a type of machine learning and data mining that uses unlabeled data to train models. It is a form of unsupervised learning, where the model is trained to learn from the data without the need for labels or annotations. Self-supervised learning algorithms are used to learn representations of data, such as images, text, and audio. These representations can then be used for downstream tasks such as classification, object detection, and natural language processing. Self-supervised learning has become increasingly popular in recent years due to its ability to learn from large amounts of unlabeled data. This has enabled the development of more accurate models for a variety of tasks. Some companies in the self-supervised learning market include Google, Microsoft, Facebook, Amazon, IBM, and Apple. Show Less Read more