9781633439894 - knowledge graphs and llms in action di negro, alessandro; kus, vlastimil; futia, giuseppe; montagna, fabio (21 risultati)

Knowledge Graphs and Llms in Action
Negro, Alessandro; Kus, Vlastimil; Futia, Giuseppe; Montagna, Fabio
- Brossura
Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 54,22
EUR 2,28 spedizioneSpedito in U.S.A.Quantità: 9 disponibili
Condizione: New.

- Brossura
Da: BargainBookStores, Grand Rapids, MI, U.S.A.BargainBookStores
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 56,58
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
- Brossura
Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
Contatta il venditoreVenditore con 5 stelleCondizione: Usato - Come nuovo
EUR 58,10
EUR 2,28 spedizioneSpedito in U.S.A.Quantità: 9 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
- Brossura
Da: California Books, Miami, FL, U.S.A.California Books
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 62,25
Spedizione gratuitaSpedito in U.S.A.Quantità: 18 disponibili
Condizione: New.

- Brossura
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 64,07
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.

- Brossura
Da: Rarewaves USA, HEBRON, KY, U.S.A.Rarewaves USA
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 68,42
Spedizione gratuitaSpedito in U.S.A.Quantità: 4 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.

- Brossura
Da: Russell Books, Victoria, BC, CanadaRussell Books
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 51,22
EUR 17,26 spedizioneSpedito da Canada a U.S.A.Quantità: 18 disponibili
paperback. Condizione: New. Special order direct from the distributor.

- Brossura
Da: Rarewaves.com USA, London, LONDO, Regno UnitoRarewaves.com USA
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 79,41
Spedizione gratuitaSpedito da Regno Unito a U.S.A.Quantità: 3 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.

Knowledge Graphs and Llms in Action
Negro, Alessandro; Kus, Vlastimil; Futia, Giuseppe; Montagna, Fabio
- Brossura
Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK
Contatta il venditoreVenditore con 5 stelleCondizione: Usato - Come nuovo
EUR 65,21
EUR 17,53 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 9 disponibili
Condizione: As New. Unread book in perfect condition.

- 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 73,93
EUR 9,50 spedizioneSpedito da Irlanda a U.S.A.Quantità: Più di 20 disponibili
Condizione: New. 2026. 1st Edition. paperback. . . . . .

Knowledge Graphs and Llms in Action
Negro, Alessandro; Kus, Vlastimil; Futia, Giuseppe; Montagna, Fabio
- Brossura
Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 68,50
EUR 17,53 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 9 disponibili
Condizione: New.

Knowledge Graphs and Llms in Action
Negro, Alessandro/ Kus, Vlastimil/ Futia, Giuseppe/ Montagna, Fabio
- Brossura
Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 80,92
EUR 14,61 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
- Brossura
Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 80,92
EUR 14,61 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 2 disponibili
Paperback. Condizione: Brand New. 425 pages. 9.26x7.38x9.25 inches. In Stock.

- Brossura
Da: THE SAINT BOOKSTORE, Southport, Regno UnitoTHE SAINT BOOKSTORE
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 73,80
EUR 22,31 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 7 disponibili
Paperback / softback. Condizione: New. New copy - Usually dispatched within 4 working days.

- Brossura
Da: Kennys Bookstore, Olney, MD, U.S.A.Kennys Bookstore
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 91,93
EUR 9,07 spedizioneSpedito in U.S.A.Quantità: Più di 20 disponibili
Condizione: New. 2026. 1st Edition. paperback. . . . . . Books ship from the US and Ireland.

Knowledge Graphs and LLMs in Action
Negro, Alessandro; Kus, Vlastimil; Futia, Giuseppe; Montagna, Fabio
- Brossura
Da: Books Puddle, New York, NY, U.S.A.Books Puddle
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 102,45
EUR 3,45 spedizioneSpedito in U.S.A.Quantità: 1 disponibili
Condizione: New.

Knowledge Graphs and LLMs in Action
Negro, Alessandro; Kus, Vlastimil; Futia, Giuseppe; Montagna, Fabio
- Brossura
Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 103,32
EUR 7,60 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 1 disponibili
Condizione: New.

- Brossura
Da: Rarewaves USA United, HEBRON, KY, U.S.A.Rarewaves USA United
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 70,47
EUR 43,17 spedizioneSpedito in U.S.A.Quantità: 3 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.

- Brossura
Da: CitiRetail, Stevenage, Regno UnitoCitiRetail
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 75,82
EUR 43,24 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.

- Brossura
Da: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 112,60
EUR 31,95 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.

- Brossura
Da: Rarewaves.com UK, London, Regno UnitoRarewaves.com UK
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 76,82
EUR 75,96 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 3 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.