The Science Behind Self-Supervised Learning скачать в хорошем качестве

The Science Behind Self-Supervised Learning

Manfredo Atzori, scientific coordinator of the HEREDITARY project, explains how Self-Supervised Learning allows models to learn from large amounts of raw data by predicting the missing information, resulting in significant vector embeddings that detect relevant similarities between concepts. In HEREDITARY, these embeddings will be further scaled to multimodal biomedical data to reveal relations, clusters and other structures between patients. This approach could help identify non-supervised subgroups of neurodegenerative diseases like Parkinson’s, improving understanding of disease variants and enabling better prognosis. Don't forget to like 👍, comment 💬, and subscribe 🔔 to stay updated with our latest videos and developments.