Multimodal Embeddings

- Foundations of multimodal representation learning - Text, image, audio, video embeddings - Contrastive learning for cross-modal alignment - Shared latent spaces across modalities - Vision encoders and patch tokenization - Transformer encoders for text meaning - Audio preprocessing and spectral features - Time-series tokenization via SAX or VQ - Fusion modules for modality alignment - Cross-attention for integrated reasoning - Zero-shot retrieval and multimodal search - Real-world multimodal applications overview