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William Smith
KenLM
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7660679KenLMhttps://www.gandhi.com.mx/kenlm-6610000974368/phttps://gandhi.vtexassets.com/arquivos/ids/7287969/image.jpg?v=638896827734330000187187MXNGandhiInStock/Ebooks/<p>"KenLM: Efficient Language Modeling in Practice"</p><p>KenLM: Efficient Language Modeling in Practice presents a comprehensive and authoritative exploration of statistical language modeling, with a dedicated focus on KenLMone of the most widely adopted open-source toolkits for n-gram language modeling. The book begins by outlining the foundational theory behind language modeling, delving into the principles of n-gram models, probability estimation, and smoothing techniques. It contextualizes the role of language models across critical NLP applications, providing clarity on their evaluation, challenges in scaling, and the benchmarks that define state-of-the-art performance.</p><p>Moving beyond theory, the book offers a meticulous examination of the KenLM architecture, emphasizing its design philosophy centered on efficiency and extensibility. Readers are guided through advanced data structures such as tries and hash tables, alongside optimization techniques for memory mapping, input/output performance, concurrency, and API design. Practical sections detail how KenLM manages large-scale datasets, supports both batch and real-time querying, and delivers low-latency, resource-efficient operation at scalequalities essential for both research and production environments.</p><p>The later chapters address the full lifecycle of language model development and deployment with KenLM. Topics encompass scalable model building pipelines, storage and compression strategies, advanced querying and scoring techniques, as well as best practices for integration, deployment, and operational security. The book concludes by surveying avenues for customization, community collaboration, and ongoing research trends, underlining KenLMs adaptability in multilingual, hybrid, and next-generation NLP systems. This self-contained volume is essential reading for engineers, researchers, and practitioners seeking a rigorous, practical guide to efficient language modeling in modern applications.</p>...7268205KenLM187187https://www.gandhi.com.mx/kenlm-6610000974368/phttps://gandhi.vtexassets.com/arquivos/ids/7287969/image.jpg?v=638896827734330000InStockMXN99999DIEbook20256610000974368_W3siaWQiOiI3MWIwODZkNy1lNGQzLTQzNTUtODQwOS02YTdlZGU1YTRlZTQiLCJsaXN0UHJpY2UiOjE4NywiZGlzY291bnQiOjAsInNlbGxpbmdQcmljZSI6MTg3LCJpbmNsdWRlc1RheCI6dHJ1ZSwicHJpY2VUeXBlIjoiSXBwIiwiY3VycmVuY3kiOiJNWE4iLCJmcm9tIjoiMjAyNS0wOC0wMVQyMDowMDowMFoiLCJyZWdpb24iOiJNWCIsImlzUHJlb3JkZXIiOmZhbHNlfV0=6610000974368_<p>"KenLM: Efficient Language Modeling in Practice"</p><p>KenLM: Efficient Language Modeling in Practice presents a comprehensive and authoritative exploration of statistical language modeling, with a dedicated focus on KenLMone of the most widely adopted open-source toolkits for n-gram language modeling. The book begins by outlining the foundational theory behind language modeling, delving into the principles of n-gram models, probability estimation, and smoothing techniques. It contextualizes the role of language models across critical NLP applications, providing clarity on their evaluation, challenges in scaling, and the benchmarks that define state-of-the-art performance.</p><p>Moving beyond theory, the book offers a meticulous examination of the KenLM architecture, emphasizing its design philosophy centered on efficiency and extensibility. Readers are guided through advanced data structures such as tries and hash tables, alongside optimization techniques for memory mapping, input/output performance, concurrency, and API design. Practical sections detail how KenLM manages large-scale datasets, supports both batch and real-time querying, and delivers low-latency, resource-efficient operation at scalequalities essential for both research and production environments.</p><p>The later chapters address the full lifecycle of language model development and deployment with KenLM. Topics encompass scalable model building pipelines, storage and compression strategies, advanced querying and scoring techniques, as well as best practices for integration, deployment, and operational security. The book concludes by surveying avenues for customization, community collaboration, and ongoing research trends, underlining KenLMs adaptability in multilingual, hybrid, and next-generation NLP systems. This self-contained volume is essential reading for engineers, researchers, and practitioners seeking a rigorous, practical guide to efficient language modeling in modern applications.</p>...6610000974368_HiTeX Presslibro_electonico_6610000974368_6610000974368William SmithInglésMéxicohttps://getbook.kobo.com/koboid-prod-public/content2connect_drm-epub-ddf9bde2-cd93-49f2-8255-3f3704b680cf.epub2025-07-24T00:00:00+00:00HiTeX Press