This is an open-access textbook on neural networks and large language models in NLP. It covers foundational machine learning concepts, neural network architectures including RNNs, CNNs, and Transformers, as well as LLM-specific topics such as pre-training, prompting, and alignment. Chapters are drawn from published research papers and include downloadable PDF materials.