Artificial intelligence in the context of digital marketing communication



natural language processing with classification and vector spaces github :: 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.





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