Machine Learning and Natural Language Processing (Paperback)
Language: English
Published by Datajoyai, 2026
- Softcover
- New

Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail
AbeBooks seller since October 12, 2005
Condition: New
US$ 60.89
Quantity: 1 available
Add to basketItem description from seller
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.…
Seller Inventory # 9781969233395
- Title
- Machine Learning and Natural Language Processing (Paperback)
- Author
- Kimberly Seefeld
- Publisher
- Datajoyai
- Publication year
- 2026
- Condition
- new
- Binding
- Paperback
- Language
- English
- ISBN 10
- 1969233397
- ISBN 13
- 9781969233395
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 www.datajoyai.com.
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.
"Synopsis" may belong to another edition of this title.
Grand Eagle Retail
Bensenville, IL, U.S.A.
AbeBooks seller since October 12, 2005
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