natural language processing in soft computing :: Article Creator CSCA 5832: Fundamentals Of Natural Language Processing Duration: 7 hours, 18 minutes This final week explores how words can be represented as vectors in a high-dimensional space, allowing computational models to capture semantic relationships between words. You will learn about both sparse and dense vector representations, including TF-IDF, Pointwise Mutual Information (PMI), Latent Semantic Analysis (LSA), and Word2Vec. The module also covers techniques for evaluating and applying word embeddings. SFU Natural Language Laboratory Natural Language Processing (NLP) is the automatic analysis of human languages such as English, Korean, etc. By computer algorithms. Unlike programming languages where the structure and meaning of programs is easy to encode, human languages provide an interesting challenge, both in terms of its analysis and the learning of language from observations. I...