9781633439894 - knowledge graphs and llms in action di negro, alessandro; kus, vlastimil; futia, giuseppe; montagna, fabio (25 risultati)
Lingua: Inglese
Editore: Manning Publications 2025
Serie: In Action, Libro 159 di 182. Libro 159 di 182 - In Action
- Brossura
Da: ThriftBooks-Dallas, Dallas, TX, U.S.A.ThriftBooks-Dallas
Contatta il venditoreVenditore con 5 stelleCondizione: Usato - Molto buono
EUR 40,36
Spedizione gratuitaSpedito in U.S.A.Quantità: 1 disponibili
Paperback. Condizione: 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
Lingua: Inglese
Editore: Manning 2025
Serie: In Action, Libro 159 di 182. Libro 159 di 182 - In Action
- Brossura
Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 54,58
EUR 2,29 spedizioneSpedito in U.S.A.Quantità: 7 disponibili
Condizione: New.
Lingua: Inglese
Editore: Manning Publications 11/18/2025 2025
Serie: In Action, Libro 159 di 182. Libro 159 di 182 - In Action
- Brossura
Da: BargainBookStores, Grand Rapids, MI, U.S.A.BargainBookStores
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 56,95
Spedizione gratuitaSpedito in U.S.A.Quantità: 4 disponibili
Paperback or Softback. Condizione: New. Knowledge Graphs and Llms in Action. Book.
Knowledge Graphs and Llms in Action
Negro, Alessandro; Kus, Vlastimil; Futia, Giuseppe; Montagna, Fabio
Lingua: Inglese
Editore: Manning 2025
Serie: In Action, Libro 159 di 182. Libro 159 di 182 - In Action
- Brossura
Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
Contatta il venditoreVenditore con 5 stelleCondizione: Usato - Come nuovo
EUR 56,50
EUR 2,29 spedizioneSpedito in U.S.A.Quantità: 7 disponibili
Condizione: 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
Lingua: Inglese
Editore: Manning 2025
Serie: In Action, Libro 159 di 182. Libro 159 di 182 - In Action
- Brossura
Da: California Books, Miami, FL, U.S.A.California Books
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 59,08
Spedizione gratuitaSpedito in U.S.A.Quantità: Più di 20 disponibili
Condizione: New.
Lingua: Inglese
Editore: Pearson Education 2025
Serie: In Action, Libro 159 di 182. Libro 159 di 182 - In Action
- Brossura
Da: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 59,51
Spedizione gratuitaSpedito in U.S.A.Quantità: 15 disponibili
PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
Lingua: Inglese
Editore: Manning Publications, US 2025
Serie: In Action, Libro 159 di 182. Libro 159 di 182 - In Action
- Brossura
Da: Rarewaves.com USA, London, LONDO, Regno UnitoRarewaves.com USA
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 60,01
Spedizione gratuitaSpedito da Regno Unito a U.S.A.Quantità: 2 disponibili
Paperback. Condizione: 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…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.
Lingua: Inglese
Editore: Pearson Education 2025
Serie: In Action, Libro 159 di 182. Libro 159 di 182 - In Action
- Brossura
Da: PBShop.store UK, Fairford, GLOS, Regno UnitoPBShop.store UK
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 53,00
EUR 7,81 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 15 disponibili
PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
Lingua: Inglese
Editore: Manning Publications, New York 2025
Serie: In Action, Libro 159 di 182. Libro 159 di 182 - In Action
- Brossura
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 64,48
Spedizione gratuitaSpedito in U.S.A.Quantità: 1 disponibili
Paperback. Condizione: 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…that 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.
Lingua: Inglese
Editore: Manning Publications, US 2025
Serie: In Action, Libro 159 di 182. Libro 159 di 182 - In Action
- Brossura
Da: Rarewaves USA, OSWEGO, IL, U.S.A.Rarewaves USA
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 68,86
Spedizione gratuitaSpedito in U.S.A.Quantità: 9 disponibili
Paperback. Condizione: 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…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.
Lingua: Inglese
Editore: Manning 2025
Serie: In Action, Libro 159 di 182. Libro 159 di 182 - In Action
- Brossura
Da: Russell Books, Victoria, BC, CanadaRussell Books
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 51,55
EUR 17,37 spedizioneSpedito da Canada a U.S.A.Quantità: Più di 20 disponibili
paperback. Condizione: New. Special order direct from the distributor.
Knowledge Graphs and Llms in Action
Negro, Alessandro; Kus, Vlastimil; Futia, Giuseppe; Montagna, Fabio
Lingua: Inglese
Editore: Manning 2025
Serie: In Action, Libro 159 di 182. Libro 159 di 182 - In Action
- Brossura
Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 52,96
EUR 17,34 spedizioneSpedito da Regno Unito a U.S.A.Quantità: Più di 20 disponibili
Condizione: New.
Knowledge Graphs and Llms in Action
Negro, Alessandro; Kus, Vlastimil; Futia, Giuseppe; Montagna, Fabio
Lingua: Inglese
Editore: Manning 2025
Serie: In Action, Libro 159 di 182. Libro 159 di 182 - In Action
- Brossura
Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK
Contatta il venditoreVenditore con 5 stelleCondizione: Usato - Come nuovo
EUR 58,00
EUR 17,34 spedizioneSpedito da Regno Unito a U.S.A.Quantità: Più di 20 disponibili
Condizione: As New. Unread book in perfect condition.
Lingua: Inglese
Editore: Manning Publications 2025
Serie: In Action, Libro 159 di 182. Libro 159 di 182 - In Action
- Brossura
Da: THE SAINT BOOKSTORE, Southport, , Regno UnitoTHE SAINT BOOKSTORE
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 52,98
EUR 22,07 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 4 disponibili
Paperback / softback. Condizione: New. New copy - Usually dispatched within 2 working days.
Lingua: Inglese
Editore: Manning Publications 2026
Serie: In Action, Libro 159 di 182. Libro 159 di 182 - In Action
- Brossura
- Prima edizione
Da: Kennys Bookshop and Art Galleries Ltd., Galway, GY, IrlandaKennys Bookshop and Art Galleries Ltd.
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 72,52
EUR 10,50 spedizioneSpedito da Irlanda a U.S.A.Quantità: 2 disponibili
Condizione: New. 2026. 1st Edition. paperback. . . . . .
Knowledge Graphs and Llms in Action
Negro, Alessandro/ Kus, Vlastimil/ Futia, Giuseppe/ Montagna, Fabio
Lingua: Inglese
Editore: Manning Pubns Co 2025
Serie: In Action, Libro 159 di 182. Libro 159 di 182 - In Action
- Brossura
Da: Revaluation Books, Exeter, , Regno UnitoRevaluation Books
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 75,41
EUR 14,45 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 2 disponibili
Paperback. Condizione: 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
Lingua: Inglese
Editore: Manning Pubns Co 2025
Serie: In Action, Libro 159 di 182. Libro 159 di 182 - In Action
- Brossura
Da: Revaluation Books, Exeter, , Regno UnitoRevaluation Books
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 81,16
EUR 14,45 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 2 disponibili
Paperback. Condizione: 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
Lingua: Inglese
Editore: Manning Pubns Co 2025
Serie: In Action, Libro 159 di 182. Libro 159 di 182 - In Action
- Brossura
Da: Revaluation Books, Exeter, , Regno UnitoRevaluation Books
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 81,16
EUR 14,45 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 2 disponibili
Paperback. Condizione: Brand New. 425 pages. 9.26x7.38x9.25 inches. In Stock.
Lingua: Inglese
Editore: Manning Publications 2025
Serie: In Action, Libro 159 di 182. Libro 159 di 182 - In Action
- Brossura
Da: Kennys Bookstore, Olney, MD, U.S.A.Kennys Bookstore
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 90,41
EUR 9,13 spedizioneSpedito in U.S.A.Quantità: 2 disponibili
Condizione: New. 2026. 1st Edition. paperback. . . . . . Books ship from the US and Ireland.
Lingua: Inglese
Editore: Manning 2025
Serie: In Action, Libro 159 di 182. Libro 159 di 182 - In Action
- Brossura
Da: Speedyhen, Hertfordshire, Regno UnitoSpeedyhen
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 55,71
EUR 47,39 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 2 disponibili
Condizione: NEW.
Lingua: Inglese
Editore: Manning Publications, New York 2025
Serie: In Action, Libro 159 di 182. Libro 159 di 182 - In Action
- Brossura
Da: CitiRetail, Stevenage, Regno UnitoCitiRetail
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 63,68
EUR 42,77 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 1 disponibili
Paperback. Condizione: 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…that 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.
Lingua: Inglese
Editore: Manning Publications, US 2025
Serie: In Action, Libro 159 di 182. Libro 159 di 182 - In Action
- Brossura
Da: Rarewaves USA United, OSWEGO, IL, U.S.A.Rarewaves USA United
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 70,47
EUR 43,45 spedizioneSpedito in U.S.A.Quantità: 9 disponibili
Paperback. Condizione: 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…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.
Lingua: Inglese
Editore: Manning Publications, US 2025
Serie: In Action, Libro 159 di 182. Libro 159 di 182 - In Action
- Brossura
Da: Rarewaves.com UK, London, Regno UnitoRarewaves.com UK
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 55,83
EUR 75,13 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 2 disponibili
Paperback. Condizione: 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…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.
Lingua: Inglese
Editore: Manning Publications Dez 2025 2025
Serie: In Action, Libro 159 di 182. Libro 159 di 182 - In Action
- Brossura
Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 71,19
EUR 64,08 spedizioneSpedito da Germania a U.S.A.Quantità: 1 disponibili
Taschenbuch. Condizione: 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.
Lingua: Inglese
Editore: Manning Publications, New York 2025
Serie: In Action, Libro 159 di 182. Libro 159 di 182 - In Action
- Brossura
Da: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 106,95
EUR 32,16 spedizioneSpedito da Australia a U.S.A.Quantità: 1 disponibili
Paperback. Condizione: 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…that 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.
