Isbn: 9781969233395 - machine learning and natural language processing: student edition (8 resultados)

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Librería: BargainBookStores, Grand Rapids, MI, Estados Unidos de AmericaBargainBookStores
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Paperback or Softback. Condición: New. Machine Learning and Natural Language Processing. Book.

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Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de AmericaPBShop.store US
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Librería: PBShop.store UK, Fairford, GLOS, Reino UnidoPBShop.store UK
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Idioma: Inglés
Editorial: Datajoyai, 2026
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Librería: California Books, Miami, FL, Estados Unidos de AmericaCalifornia Books
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Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de AmericaGrand Eagle Retail
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EUR 55,31
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Paperback. Condición: new. Paperback. Machine Learning and Natural Language Processing provides an accessible, applied introduction to machine learning (ML) and natural language processing (NLP) for students, educators, and business professionals. Designed for introductory college courses in analytics, artificial intelligence, and data science, this text focuses on practical understanding rather than advanced mathematics.Readers learn how machine learning systems identify patterns in data, make predictions, support decision-making, and automate business processes. Topics include supervised and unsupervised learning, classification, regression, recommendation systems, optimization, model evaluation, performance metrics, bias, fairness, and responsible AI practices.The NLP portion of the book explores how computers process and analyze human language. Students learn text preprocessing, tokenization, stopword removal, lemmatization, TF-IDF, word embeddings, sentiment analysis, topic modeling, named entity recognition, conversational AI, text summarization, and generative AI applications.Throughout the text, real-world examples demonstrate how organizations use ML and NLP to improve customer experiences, streamline operations, analyze feedback, and support strategic decisions. Hands-on labs and guided activities help students apply concepts using modern analytics tools and datasets. Resources available at Written in a clear, student-friendly style, this book bridges the gap between theory and practice while emphasizing ethical considerations, model interpretability, and human oversight. It is ideal for introductory courses in machine learning, artificial intelligence, natural language processing, business analytics, and applied data science. Machine Learning and Natural Language Processing: Student Edition provides a hands-on introduction to machine learning and NLP for real-world applications. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

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Librería: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
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EUR 58,36
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Paperback. Condición: new. Paperback. Machine Learning and Natural Language Processing provides an accessible, applied introduction to machine learning (ML) and natural language processing (NLP) for students, educators, and business professionals. Designed for introductory college courses in analytics, artificial intelligence, and data science, this text focuses on practical understanding rather than advanced mathematics.Readers learn how machine learning systems identify patterns in data, make predictions, support decision-making, and automate business processes. Topics include supervised and unsupervised learning, classification, regression, recommendation systems, optimization, model evaluation, performance metrics, bias, fairness, and responsible AI practices.The NLP portion of the book explores how computers process and analyze human language. Students learn text preprocessing, tokenization, stopword removal, lemmatization, TF-IDF, word embeddings, sentiment analysis, topic modeling, named entity recognition, conversational AI, text summarization, and generative AI applications.Throughout the text, real-world examples demonstrate how organizations use ML and NLP to improve customer experiences, streamline operations, analyze feedback, and support strategic decisions. Hands-on labs and guided activities help students apply concepts using modern analytics tools and datasets. Resources available at Written in a clear, student-friendly style, this book bridges the gap between theory and practice while emphasizing ethical considerations, model interpretability, and human oversight. It is ideal for introductory courses in machine learning, artificial intelligence, natural language processing, business analytics, and applied data science. Machine Learning and Natural Language Processing: Student Edition provides a hands-on introduction to machine learning and NLP for real-world applications. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

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Librería: CitiRetail, Stevenage, Reino UnidoCitiRetail
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EUR 51,66
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Paperback. Condición: new. Paperback. Machine Learning and Natural Language Processing provides an accessible, applied introduction to machine learning (ML) and natural language processing (NLP) for students, educators, and business professionals. Designed for introductory college courses in analytics, artificial intelligence, and data science, this text focuses on practical understanding rather than advanced mathematics.Readers learn how machine learning systems identify patterns in data, make predictions, support decision-making, and automate business processes. Topics include supervised and unsupervised learning, classification, regression, recommendation systems, optimization, model evaluation, performance metrics, bias, fairness, and responsible AI practices.The NLP portion of the book explores how computers process and analyze human language. Students learn text preprocessing, tokenization, stopword removal, lemmatization, TF-IDF, word embeddings, sentiment analysis, topic modeling, named entity recognition, conversational AI, text summarization, and generative AI applications.Throughout the text, real-world examples demonstrate how organizations use ML and NLP to improve customer experiences, streamline operations, analyze feedback, and support strategic decisions. Hands-on labs and guided activities help students apply concepts using modern analytics tools and datasets. Resources available at Written in a clear, student-friendly style, this book bridges the gap between theory and practice while emphasizing ethical considerations, model interpretability, and human oversight. It is ideal for introductory courses in machine learning, artificial intelligence, natural language processing, business analytics, and applied data science. Machine Learning and Natural Language Processing: Student Edition provides a hands-on introduction to machine learning and NLP for real-world applications. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

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Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
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EUR 68,82
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Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering.