The core of the book covers foundational and advanced vector-space techniques and embeddings-Bag-of-Words, TF-IDF, LSA, LDA, Word2Vec, FastText, and Doc2Vec-alongside practical guidance on preprocessing, corpus management, model evaluation, interpretability, and hyperparameter optimization. Each concept is grounded in reproducible examples and industrial best practices so practitioners gain both the theoretical background and the hands-on skills needed to deploy reliable, performant models.
Beyond core text processing, the book explores multimodal and domain-specific workflows, semantic search, and integration with diverse data sources and systems. Chapters on production hardening address observability, security, parallel computation, and ethical AI, while forward-looking guidance covers custom model extensions, knowledge graph integration, and using Gensim in concert with large language models-making this an essential resource for engineers and researchers building responsible, scalable NLP solutions.
Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, CY, CZ, D, DK, EW, E, FIN, F, GR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.