Overview

Multimodal deep learning is an approach in machine learning that focuses on processing and understanding data from multiple modalities or sources, such as text, images, audio, and more. This approach aims to leverage the complementary information provided by these different data types to improve the accuracy and richness of machine learning models –by gpt

• GitHub - pliang279/awesome-multimodal-ml: Reading list for research topics in multimodal machine learning
• MML Tutorial - Schedule
• CLIP: Connecting text and images
• Contrastive Learning - Papers With Code