Learn to implement a minimal neural network toolkit for NLP in this lecture from CMU's Neural Networks for NLP course. Explore model definition, graph creation, forward and backward calculations, and parameter updates. Gain insights into neural network frameworks, deep Sibo models, and numerical computation. Discover how to work with tensors, create model code, handle weights and input dimensions, and manage computation graphs. Master the process of backward propagation and parameter updating in this comprehensive overview of building neural network tools for natural language processing tasks.