Provides an overview of Natural Language Processing, focusing on transformers, tokenization, and self-attention mechanisms for effective language analysis and synthesis.
Explores integrated risk management, disaster costs, mitigation, and crisis management, analyzing the impact of disasters and the distribution of costs.
Explores chemical reaction prediction using generative models and molecular transformers, emphasizing the importance of molecular language processing and stereochemistry.
Explores the Transformer model, from recurrent models to attention-based NLP, highlighting its key components and significant results in machine translation and document generation.