9781633439894 - knowledge graphs and llms in action: build ai systems using connected data de negro, alessandro (25 resultados)
Idioma: Inglés
Editorial: Manning Publications 2025
Serie: In Action, Libro 159 de 182. Libro 159 de 182 - In Action
- Tapa blanda
Librería: ThriftBooks-Dallas, Dallas, TX, Estados Unidos de AmericaThriftBooks-Dallas
Contactar con el vendedorVendedor de 5 estrellasCondición: Usado - Bueno
EUR 40,02
Gastos de envío gratisSe envía dentro de Estados Unidos de AmericaCantidad disponible: 1 disponibles
Paperback. Condición: Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less.
Knowledge Graphs and Llms in Action
Negro, Alessandro; Kus, Vlastimil; Futia, Giuseppe; Montagna, Fabio
Idioma: Inglés
Editorial: Manning 2025
Serie: In Action, Libro 159 de 182. Libro 159 de 182 - In Action
- Tapa blanda
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de AmericaGreatBookPrices
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 54,12
Envío por EUR 2,28Se envía dentro de Estados Unidos de AmericaCantidad disponible: 7 disponibles
Condición: New.
Idioma: Inglés
Editorial: Manning Publications 11/18/2025 2025
Serie: In Action, Libro 159 de 182. Libro 159 de 182 - In Action
- Tapa blanda
Librería: BargainBookStores, Grand Rapids, MI, Estados Unidos de AmericaBargainBookStores
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 56,47
Gastos de envío gratisSe envía dentro de Estados Unidos de AmericaCantidad disponible: 4 disponibles
Paperback or Softback. Condición: New. Knowledge Graphs and Llms in Action. Book.
Knowledge Graphs and Llms in Action
Negro, Alessandro; Kus, Vlastimil; Futia, Giuseppe; Montagna, Fabio
Idioma: Inglés
Editorial: Manning 2025
Serie: In Action, Libro 159 de 182. Libro 159 de 182 - In Action
- Tapa blanda
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de AmericaGreatBookPrices
Contactar con el vendedorVendedor de 5 estrellasCondición: Usado - Como Nuevo
EUR 56,06
Envío por EUR 2,28Se envía dentro de Estados Unidos de AmericaCantidad disponible: 7 disponibles
Condición: As New. Unread book in perfect condition.
Knowledge Graphs and LLMs in Action: Build AI systems using connected data
Negro, Alessandro; Kus, Vlastimil; Futia, Giuseppe; Montagna, Fabio
Idioma: Inglés
Editorial: Manning 2025
Serie: In Action, Libro 159 de 182. Libro 159 de 182 - In Action
- Tapa blanda
Librería: California Books, Miami, FL, Estados Unidos de AmericaCalifornia Books
Contactar con el vendedorVendedor de 4 estrellasCondición: Nuevo
EUR 58,59
Gastos de envío gratisSe envía dentro de Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Condición: New.
Idioma: Inglés
Editorial: Pearson Education 2025
Serie: In Action, Libro 159 de 182. Libro 159 de 182 - In Action
- Tapa blanda
Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de AmericaPBShop.store US
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 59,01
Gastos de envío gratisSe envía dentro de Estados Unidos de AmericaCantidad disponible: 15 disponibles
PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.
Idioma: Inglés
Editorial: Manning Publications, US 2025
Serie: In Action, Libro 159 de 182. Libro 159 de 182 - In Action
- Tapa blanda
Librería: Rarewaves.com USA, London, LONDO, Reino UnidoRarewaves.com USA
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 60,03
Gastos de envío gratisSe envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 2 disponibles
Paperback. Condición: New. Data overload, disconnected context, and stalled machine learning results are common frustrations for data teams. Even with vast datasets and advanced models, insights remain elusive when information is scattered and relationships are unclear. What if you could structure your data in a way that gives i…t meaning, connects the dots, and powers smarter, faster learning? By building knowledge graphs that integrate with large language models, you can transform disconnected information into actionable, context-rich intelligence that drives real results. Iterative top-down modeling: Aligns every graph decision with clear business questions. Ontology and taxonomy starters: Jump-start graph design from your existing structured data. Python code walk-throughs: Let you replicate techniques on day one, no guesswork. GNN and BERT integration: Upgrade graphs with deep learning for smarter reasoning and predictions. Real healthcare and policing cases: Prove scalability on messy, high-stakes datasets. Knowledge Graphs and LLMs in Action by GraphAware scientists Dr. Alessandro Negro and colleagues delivers a code-rich softcover reference that unites cutting-edge research with field-tested engineering practice. Starting with business questions, you model ontologies, import varied sources, then iteratively expand your graph. Later chapters layer GNNs, transformers, and reasoning algorithms, showing complete pipelines on full-scale datasets. You will leave with repeatable workflows, reusable code, and the confidence to connect fragmented data into intelligent, context-aware applications. Stop guessing; start delivering measurable machine learning impact.
Idioma: Inglés
Editorial: Pearson Education 2025
Serie: In Action, Libro 159 de 182. Libro 159 de 182 - In Action
- Tapa blanda
Librería: PBShop.store UK, Fairford, GLOS, Reino UnidoPBShop.store UK
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 53,15
Envío por EUR 7,84Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 15 disponibles
PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.
Idioma: Inglés
Editorial: Manning Publications, New York 2025
Serie: In Action, Libro 159 de 182. Libro 159 de 182 - In Action
- Tapa blanda
Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de AmericaGrand Eagle Retail
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 63,95
Gastos de envío gratisSe envía dentro de Estados Unidos de AmericaCantidad disponible: 1 disponibles
Paperback. Condición: new. Paperback. Data overload, disconnected context, and stalled machine learning results are common frustrations for data teams. Even with vast datasets and advanced models, insights remain elusive when information is scattered and relationships are unclear. What if you could structure your data in a way t…hat gives it meaning, connects the dots, and powers smarter, faster learning? By building knowledge graphs that integrate with large language models, you can transform disconnected information into actionable, context-rich intelligence that drives real results. Iterative top-down modeling: Aligns every graph decision with clear business questions. Ontology and taxonomy starters: Jump-start graph design from your existing structured data. Python code walk-throughs: Let you replicate techniques on day one, no guesswork. GNN and BERT integration: Upgrade graphs with deep learning for smarter reasoning and predictions. Real healthcare and policing cases: Prove scalability on messy, high-stakes datasets. Knowledge Graphs and LLMs in Action by GraphAware scientists Dr. Alessandro Negro and colleagues delivers a code-rich softcover reference that unites cutting-edge research with field-tested engineering practice. Starting with business questions, you model ontologies, import varied sources, then iteratively expand your graph. Later chapters layer GNNs, transformers, and reasoning algorithms, showing complete pipelines on full-scale datasets. You will leave with repeatable workflows, reusable code, and the confidence to connect fragmented data into intelligent, context-aware applications. Stop guessing; start delivering measurable machine learning impact. Knowledge graphs represent a real paradigm shift in the way that machines can understand data by effectively modeling the contextual information thats vital for human knowledge. Theyre poised to help revolutionize data analysis and machine learning, with applications ranging from search engines to e-commerce and more. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Idioma: Inglés
Editorial: Manning Publications, US 2025
Serie: In Action, Libro 159 de 182. Libro 159 de 182 - In Action
- Tapa blanda
Librería: Rarewaves USA, OSWEGO, IL, Estados Unidos de AmericaRarewaves USA
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 68,29
Gastos de envío gratisSe envía dentro de Estados Unidos de AmericaCantidad disponible: 9 disponibles
Paperback. Condición: New. Data overload, disconnected context, and stalled machine learning results are common frustrations for data teams. Even with vast datasets and advanced models, insights remain elusive when information is scattered and relationships are unclear. What if you could structure your data in a way that gives i…t meaning, connects the dots, and powers smarter, faster learning? By building knowledge graphs that integrate with large language models, you can transform disconnected information into actionable, context-rich intelligence that drives real results. Iterative top-down modeling: Aligns every graph decision with clear business questions. Ontology and taxonomy starters: Jump-start graph design from your existing structured data. Python code walk-throughs: Let you replicate techniques on day one, no guesswork. GNN and BERT integration: Upgrade graphs with deep learning for smarter reasoning and predictions. Real healthcare and policing cases: Prove scalability on messy, high-stakes datasets. Knowledge Graphs and LLMs in Action by GraphAware scientists Dr. Alessandro Negro and colleagues delivers a code-rich softcover reference that unites cutting-edge research with field-tested engineering practice. Starting with business questions, you model ontologies, import varied sources, then iteratively expand your graph. Later chapters layer GNNs, transformers, and reasoning algorithms, showing complete pipelines on full-scale datasets. You will leave with repeatable workflows, reusable code, and the confidence to connect fragmented data into intelligent, context-aware applications. Stop guessing; start delivering measurable machine learning impact.
Knowledge Graphs and Llms in Action
Negro, Alessandro; Kus, Vlastimil; Futia, Giuseppe; Montagna, Fabio
Idioma: Inglés
Editorial: Manning 2025
Serie: In Action, Libro 159 de 182. Libro 159 de 182 - In Action
- Tapa blanda
Librería: GreatBookPricesUK, Woodford Green, Reino UnidoGreatBookPricesUK
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 53,11
Envío por EUR 17,39Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Condición: New.
Knowledge Graphs and Llms in Action
Negro, Alessandro; Kus, Vlastimil; Futia, Giuseppe; Montagna, Fabio
Idioma: Inglés
Editorial: Manning 2025
Serie: In Action, Libro 159 de 182. Libro 159 de 182 - In Action
- Tapa blanda
Librería: GreatBookPricesUK, Woodford Green, Reino UnidoGreatBookPricesUK
Contactar con el vendedorVendedor de 5 estrellasCondición: Usado - Como Nuevo
EUR 57,37
Envío por EUR 17,39Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Condición: As New. Unread book in perfect condition.
Idioma: Inglés
Editorial: Manning Publications 2025
Serie: In Action, Libro 159 de 182. Libro 159 de 182 - In Action
- Tapa blanda
Librería: THE SAINT BOOKSTORE, Southport, , Reino UnidoTHE SAINT BOOKSTORE
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 53,13
Envío por EUR 22,13Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 4 disponibles
Paperback / softback. Condición: New. New copy - Usually dispatched within 2 working days.
Idioma: Inglés
Editorial: Manning 2025
Serie: In Action, Libro 159 de 182. Libro 159 de 182 - In Action
- Tapa blanda
Librería: Russell Books, Victoria, BC, CanadaRussell Books
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 63,90
Envío por EUR 17,23Se envía de Canada a Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
paperback. Condición: New. Special order direct from the distributor.
Idioma: Inglés
Editorial: Manning Publications 2026
Serie: In Action, Libro 159 de 182. Libro 159 de 182 - In Action
- Tapa blanda
- Primera edición
Librería: Kennys Bookshop and Art Galleries Ltd., Galway, GY, IrlandaKennys Bookshop and Art Galleries Ltd.
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 72,52
Envío por EUR 10,50Se envía de Irlanda a Estados Unidos de AmericaCantidad disponible: 2 disponibles
Condición: New. 2026. 1st Edition. paperback. . . . . .
Knowledge Graphs and Llms in Action
Negro, Alessandro/ Kus, Vlastimil/ Futia, Giuseppe/ Montagna, Fabio
Idioma: Inglés
Editorial: Manning Pubns Co 2025
Serie: In Action, Libro 159 de 182. Libro 159 de 182 - In Action
- Tapa blanda
Librería: Revaluation Books, Exeter, , Reino UnidoRevaluation Books
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 75,62
Envío por EUR 14,49Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 2 disponibles
Paperback. Condición: Brand New. 425 pages. 9.26x7.38x9.25 inches. In Stock.
Knowledge Graphs and Llms in Action
Negro, Alessandro/ Kus, Vlastimil/ Futia, Giuseppe/ Montagna, Fabio
Idioma: Inglés
Editorial: Manning Pubns Co 2025
Serie: In Action, Libro 159 de 182. Libro 159 de 182 - In Action
- Tapa blanda
Librería: Revaluation Books, Exeter, , Reino UnidoRevaluation Books
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 81,28
Envío por EUR 14,49Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 2 disponibles
Paperback. Condición: Brand New. 425 pages. 9.26x7.38x9.25 inches. In Stock.
Knowledge Graphs and Llms in Action
Negro, Alessandro/ Kus, Vlastimil/ Futia, Giuseppe/ Montagna, Fabio
Idioma: Inglés
Editorial: Manning Pubns Co 2025
Serie: In Action, Libro 159 de 182. Libro 159 de 182 - In Action
- Tapa blanda
Librería: Revaluation Books, Exeter, , Reino UnidoRevaluation Books
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 81,28
Envío por EUR 14,49Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 2 disponibles
Paperback. Condición: Brand New. 425 pages. 9.26x7.38x9.25 inches. In Stock.
Idioma: Inglés
Editorial: Manning Publications 2025
Serie: In Action, Libro 159 de 182. Libro 159 de 182 - In Action
- Tapa blanda
Librería: Kennys Bookstore, Olney, MD, Estados Unidos de AmericaKennys Bookstore
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 89,67
Envío por EUR 9,05Se envía dentro de Estados Unidos de AmericaCantidad disponible: 2 disponibles
Condición: New. 2026. 1st Edition. paperback. . . . . . Books ship from the US and Ireland.
Idioma: Inglés
Editorial: Manning 2025
Serie: In Action, Libro 159 de 182. Libro 159 de 182 - In Action
- Tapa blanda
Librería: Speedyhen, Hertfordshire, Reino UnidoSpeedyhen
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 55,87
Envío por EUR 47,52Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 2 disponibles
Condición: NEW.
Idioma: Inglés
Editorial: Manning Publications, New York 2025
Serie: In Action, Libro 159 de 182. Libro 159 de 182 - In Action
- Tapa blanda
Librería: CitiRetail, Stevenage, Reino UnidoCitiRetail
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 63,86
Envío por EUR 42,89Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Paperback. Condición: new. Paperback. Data overload, disconnected context, and stalled machine learning results are common frustrations for data teams. Even with vast datasets and advanced models, insights remain elusive when information is scattered and relationships are unclear. What if you could structure your data in a way t…hat gives it meaning, connects the dots, and powers smarter, faster learning? By building knowledge graphs that integrate with large language models, you can transform disconnected information into actionable, context-rich intelligence that drives real results. Iterative top-down modeling: Aligns every graph decision with clear business questions. Ontology and taxonomy starters: Jump-start graph design from your existing structured data. Python code walk-throughs: Let you replicate techniques on day one, no guesswork. GNN and BERT integration: Upgrade graphs with deep learning for smarter reasoning and predictions. Real healthcare and policing cases: Prove scalability on messy, high-stakes datasets. Knowledge Graphs and LLMs in Action by GraphAware scientists Dr. Alessandro Negro and colleagues delivers a code-rich softcover reference that unites cutting-edge research with field-tested engineering practice. Starting with business questions, you model ontologies, import varied sources, then iteratively expand your graph. Later chapters layer GNNs, transformers, and reasoning algorithms, showing complete pipelines on full-scale datasets. You will leave with repeatable workflows, reusable code, and the confidence to connect fragmented data into intelligent, context-aware applications. Stop guessing; start delivering measurable machine learning impact. Knowledge graphs represent a real paradigm shift in the way that machines can understand data by effectively modeling the contextual information thats vital for human knowledge. Theyre poised to help revolutionize data analysis and machine learning, with applications ranging from search engines to e-commerce and more. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Idioma: Inglés
Editorial: Manning Publications, US 2025
Serie: In Action, Libro 159 de 182. Libro 159 de 182 - In Action
- Tapa blanda
Librería: Rarewaves USA United, OSWEGO, IL, Estados Unidos de AmericaRarewaves USA United
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 70,67
Envío por EUR 43,09Se envía dentro de Estados Unidos de AmericaCantidad disponible: 9 disponibles
Paperback. Condición: New. Data overload, disconnected context, and stalled machine learning results are common frustrations for data teams. Even with vast datasets and advanced models, insights remain elusive when information is scattered and relationships are unclear. What if you could structure your data in a way that gives i…t meaning, connects the dots, and powers smarter, faster learning? By building knowledge graphs that integrate with large language models, you can transform disconnected information into actionable, context-rich intelligence that drives real results. Iterative top-down modeling: Aligns every graph decision with clear business questions. Ontology and taxonomy starters: Jump-start graph design from your existing structured data. Python code walk-throughs: Let you replicate techniques on day one, no guesswork. GNN and BERT integration: Upgrade graphs with deep learning for smarter reasoning and predictions. Real healthcare and policing cases: Prove scalability on messy, high-stakes datasets. Knowledge Graphs and LLMs in Action by GraphAware scientists Dr. Alessandro Negro and colleagues delivers a code-rich softcover reference that unites cutting-edge research with field-tested engineering practice. Starting with business questions, you model ontologies, import varied sources, then iteratively expand your graph. Later chapters layer GNNs, transformers, and reasoning algorithms, showing complete pipelines on full-scale datasets. You will leave with repeatable workflows, reusable code, and the confidence to connect fragmented data into intelligent, context-aware applications. Stop guessing; start delivering measurable machine learning impact.
Idioma: Inglés
Editorial: Manning Publications, US 2025
Serie: In Action, Libro 159 de 182. Libro 159 de 182 - In Action
- Tapa blanda
Librería: Rarewaves.com UK, London, Reino UnidoRarewaves.com UK
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 55,99
Envío por EUR 75,34Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 2 disponibles
Paperback. Condición: New. Data overload, disconnected context, and stalled machine learning results are common frustrations for data teams. Even with vast datasets and advanced models, insights remain elusive when information is scattered and relationships are unclear. What if you could structure your data in a way that gives i…t meaning, connects the dots, and powers smarter, faster learning? By building knowledge graphs that integrate with large language models, you can transform disconnected information into actionable, context-rich intelligence that drives real results. Iterative top-down modeling: Aligns every graph decision with clear business questions. Ontology and taxonomy starters: Jump-start graph design from your existing structured data. Python code walk-throughs: Let you replicate techniques on day one, no guesswork. GNN and BERT integration: Upgrade graphs with deep learning for smarter reasoning and predictions. Real healthcare and policing cases: Prove scalability on messy, high-stakes datasets. Knowledge Graphs and LLMs in Action by GraphAware scientists Dr. Alessandro Negro and colleagues delivers a code-rich softcover reference that unites cutting-edge research with field-tested engineering practice. Starting with business questions, you model ontologies, import varied sources, then iteratively expand your graph. Later chapters layer GNNs, transformers, and reasoning algorithms, showing complete pipelines on full-scale datasets. You will leave with repeatable workflows, reusable code, and the confidence to connect fragmented data into intelligent, context-aware applications. Stop guessing; start delivering measurable machine learning impact.
Idioma: Inglés
Editorial: Manning Publications Dez 2025 2025
Serie: In Action, Libro 159 de 182. Libro 159 de 182 - In Action
- Tapa blanda
Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 71,19
Envío por EUR 64,08Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Taschenbuch. Condición: Neu. Neuware - Combine knowledge graphs with large language models to deliver powerful, reliable, and explainable AI solutions.Knowledge graphs model relationships between the objects, events, situations, and concepts in your domain so you can readily identify important patterns in your own data and make…better decisions. Paired up with large language models, they promise huge potential for working with structured and unstructured enterprise data, building recommendation systems, developing fraud detection mechanisms, delivering customer service chatbots, or more. This book provides tools and techniques for efficiently organizing data, modeling a knowledge graph, and incorporating KGs into the functioning of LLMsand vice versa. In Knowledge Graphs and LLMs in Action you will learn how to: Model knowledge graphs with an iterative top-down approach based in business needs Create a knowledge graph starting from ontologies, taxonomies, and structured data Build knowledge graphs from unstructured data sources using LLMs Use machine learning algorithms to complete your graphs and derive insights from it Reason on the knowledge graph and build KG-powered RAG systems for LLMs In Knowledge Graphs and LLMs in Action, you'll discover the theory of knowledge graphs then put them into practice with LLMs to build working intelligence systems. You'll learn to create KGs from first principles, go hands-on to develop advisor applications for real-world domains like healthcare and finance, build retrieval augmented generation for LLMs, and more. About the technology Using knowledge graphs with LLMs reduces hallucinations, enables explainable outputs, and supports better reasoning. By naturally encoding the relationships in your data, knowledge graphs help create AI systems that are more reliable and accurate, even for models that have limited domain knowledge. About the book Knowledge Graphs and LLMs in Action shows you how to introduce knowledge graphs constructed from structured and unstructured sources into LLM-powered applications and RAG pipelines. Real-world case studies for domain-specific applicationsfrom healthcare to financial crime detectionillustrate how this powerful pairing works in practice. You'll especially appreciate the expert insights on knowledge representation and reasoning strategies. What's inside Design knowledge graphs for real-world needs Build KGs from structured and unstructured data Apply machine learning to enrich, complete, and analyze graphs Pair knowledge graphs with RAG systems About the reader For ML and AI engineers, data scientists, and data engineers. Examples in Python. About the author Alessandro Negro is Chief Scientist at GraphAware and author of Graph-Powered Machine Learning. Vlastimil Kus, Giuseppe Futia, and Fabio Montagna are seasoned ML and AI professionals specializing in Knowledge Graphs, Large Language Models, and Graph Neural Networks. Table of Contents Part 1 1 Knowledge graphs and LLMs: A killer combination 2 Intelligent systems: A hybrid approach Part 2 3 Create your first knowledge graph from ontologies 4 From simple networks to multisource integration Part 3 5 Extracting domain-specific knowledge from unstructured data 6 Building knowledge graphs with large language models 7 Named entity disambiguation 8 NED with open LLMs and domain ontologies Part 4 9 Machine learning on knowledge graphs: A primer approach 10 Graph feature engineering: Manual and semiautomated approaches 11 Graph representation learning and graph neural networks 12 Node classification and link prediction with GNNs Part 5 13 Knowledge graphpowered retrieval-augmented generation 14 Asking a KG questions with natural language 15 Building a QA agent with LangGraph Get a free Elektronisches Buch (PDF or ePub) from Manning as well as access to the online liveBook format (and its AI assistant that will answer your questions in any language) when you purchase the print book.
Idioma: Inglés
Editorial: Manning Publications, New York 2025
Serie: In Action, Libro 159 de 182. Libro 159 de 182 - In Action
- Tapa blanda
Librería: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 106,92
Envío por EUR 31,89Se envía de Australia a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Paperback. Condición: new. Paperback. Data overload, disconnected context, and stalled machine learning results are common frustrations for data teams. Even with vast datasets and advanced models, insights remain elusive when information is scattered and relationships are unclear. What if you could structure your data in a way t…hat gives it meaning, connects the dots, and powers smarter, faster learning? By building knowledge graphs that integrate with large language models, you can transform disconnected information into actionable, context-rich intelligence that drives real results. Iterative top-down modeling: Aligns every graph decision with clear business questions. Ontology and taxonomy starters: Jump-start graph design from your existing structured data. Python code walk-throughs: Let you replicate techniques on day one, no guesswork. GNN and BERT integration: Upgrade graphs with deep learning for smarter reasoning and predictions. Real healthcare and policing cases: Prove scalability on messy, high-stakes datasets. Knowledge Graphs and LLMs in Action by GraphAware scientists Dr. Alessandro Negro and colleagues delivers a code-rich softcover reference that unites cutting-edge research with field-tested engineering practice. Starting with business questions, you model ontologies, import varied sources, then iteratively expand your graph. Later chapters layer GNNs, transformers, and reasoning algorithms, showing complete pipelines on full-scale datasets. You will leave with repeatable workflows, reusable code, and the confidence to connect fragmented data into intelligent, context-aware applications. Stop guessing; start delivering measurable machine learning impact. Knowledge graphs represent a real paradigm shift in the way that machines can understand data by effectively modeling the contextual information thats vital for human knowledge. Theyre poised to help revolutionize data analysis and machine learning, with applications ranging from search engines to e-commerce and more. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
