Alessandro negro (52 resultados)
Idioma: Inglés
Editorial: American Geophysical Union, 2004
Serie: Geophysical Monograph, Libro 126 de 266. Libro 126 de 266 - Geophysical Monograph
- Tapa dura
- Primera edición
Librería: Amusespot, Henderson, NV, Estados Unidos de AmericaAmusespot
Contactar con el vendedorVendedor de 5 estrellasCondición: Usado - Aceptable
EUR 36,02
Envío por EUR 3,94Se envía dentro de Estados Unidos de AmericaCantidad disponible: 1 disponibles
Hardcover. Condición: Good. 1st Edition. Very good condition. Ex-library.
Idioma: Inglés
Editorial: Manning Publications, 2025
Serie: In Action, Libro 159 de 182. Libro 159 de 182 - In Action
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Librería: ThriftBooks-Dallas, Dallas, TX, Estados Unidos de AmericaThriftBooks-Dallas
Contactar con el vendedorVendedor de 5 estrellasCondición: Usado - Bueno
EUR 41,87
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.
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Librería: Basi6 International, Irving, TX, Estados Unidos de AmericaBasi6 International
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 55,79
Gastos de envío gratisSe envía dentro de Estados Unidos de AmericaCantidad disponible: 8 disponibles
Condición: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
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Librería: Rarewaves USA, OSWEGO, IL, Estados Unidos de AmericaRarewaves USA
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 56,22
Gastos de envío gratisSe envía dentro de Estados Unidos de AmericaCantidad disponible: 10 disponibles
Paperback. Condición: New. At its core, machine learning is about efficiently identifying patterns and relationships in data. Many tasks, such as finding associations among terms so you can make accurate search recommendations or locating individuals within a social network who have similar interests, are naturally expressed as…graphs. Graph-Powered Machine Learning introduces you to graph technology concepts, highlighting the role of graphs in machine learning and big data platforms. You'll get an in-depth look at techniques including data source modeling, algorithm design, link analysis, classification, and clustering. As you master the core concepts, you'll explore three end-to-end projects that illustrate architectures, best design practices, optimization approaches, and common pitfalls. Key Features · The lifecycle of a machine learning project · Three end-to-end applications · Graphs in big data platforms · Data source modeling · Natural language processing, recommendations, and relevant search · Optimization methods Readers comfortable with machine learning basics. About the technology By organizing and analyzing your data as graphs, your applications work more fluidly with graph-centric algorithms like nearest neighbor or page rank where it's important to quickly identify and exploit relevant relationships. Modern graph data stores, like Neo4j or Amazon Neptune, are readily available tools that support graph-powered machine learning. Alessandro Negro is a Chief Scientist at GraphAware. With extensive experience in software development, software architecture, and data management, he has been a speaker at many conferences, such as Java One, Oracle Open World, and Graph Connect. He holds a Ph.D. in Computer Science and has authored several publications on graph-based machine learning.
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
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de AmericaGreatBookPrices
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 54,97
Envío por EUR 2,31Se envía dentro de Estados Unidos de AmericaCantidad disponible: Más de 20 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
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Librería: BargainBookStores, Grand Rapids, MI, Estados Unidos de AmericaBargainBookStores
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 57,36
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 57,00
Envío por EUR 2,31Se envía dentro de Estados Unidos de AmericaCantidad disponible: Más de 20 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 59,51
Gastos de envío gratisSe envía dentro de Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Condición: New.
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 61,01
Gastos de envío gratisSe envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 1 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.
- Tapa blanda
Librería: PBShop.store UK, Fairford, GLOS, Reino UnidoPBShop.store UK
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 57,13
Envío por EUR 6,88Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 12 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 64,95
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.
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Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de AmericaGrand Eagle Retail
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 66,27
Gastos de envío gratisSe envía dentro de Estados Unidos de AmericaCantidad disponible: 1 disponibles
Paperback. Condición: new. Paperback. At its core, machine learning is about efficiently identifying patterns and relationships in data. Many tasks, such as finding associations among terms so you can make accurate search recommendations or locating individuals within a social network who have similar interests, are naturally ex…pressed as graphs. Graph-Powered Machine Learning introduces you to graph technology concepts, highlighting the role of graphs in machine learning and big data platforms. Youll get an in-depth look at techniques including data source modeling, algorithm design, link analysis, classification, and clustering. As you master the core concepts, youll explore three end-to-end projects that illustrate architectures, best design practices, optimization approaches, and common pitfalls. Key Features The lifecycle of a machine learning project Three end-to-end applications Graphs in big data platforms Data source modeling Natural language processing, recommendations, and relevant search Optimization methods Readers comfortable with machine learning basics. About the technology By organizing and analyzing your data as graphs, your applications work more fluidly with graph-centric algorithms like nearest neighbor or page rank where its important to quickly identify and exploit relevant relationships. Modern graph data stores, like Neo4j or Amazon Neptune, are readily available tools that support graph-powered machine learning. Alessandro Negro is a Chief Scientist at GraphAware. With extensive experience in software development, software architecture, and data management, he has been a speaker at many conferences, such as Java One, Oracle Open World, and Graph Connect. He holds a Ph.D. in Computer Science and has authored several publications on graph-based machine learning. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Idioma: Inglés
Editorial: American Geophysical Union, 2004
Serie: Geophysical Monograph, Libro 126 de 266. Libro 126 de 266 - Geophysical Monograph
- Tapa dura
Librería: ThriftBooks-Dallas, Dallas, TX, Estados Unidos de AmericaThriftBooks-Dallas
Contactar con el vendedorVendedor de 5 estrellasCondición: Usado - Como Nuevo
EUR 66,70
Gastos de envío gratisSe envía dentro de Estados Unidos de AmericaCantidad disponible: 1 disponibles
Hardcover. Condición: As New. No Jacket. Pages are clean and are not marred by notes or folds of any kind. ~ ThriftBooks: Read More, Spend Less.
- Tapa blanda
Librería: WorldofBooks, Goring-By-Sea, WS, Reino UnidoWorldofBooks
Contactar con el vendedorVendedor de 5 estrellasCondición: Usado - Bueno
EUR 61,51
Envío por EUR 6,57Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Paperback. Condición: Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.
Mt. Etna: Volcano Laboratory (Geophysical Monograph Series)
Bonaccorso, Alessandro [Editor]; Calvari, Sonia [Editor]; Coltelli, Mauro [Editor]; Del Negro, Ciro [Editor]; Falsaperla, Susanna [Editor];
Idioma: Inglés
Editorial: American Geophysical Union, 2004
Serie: Geophysical Monograph, Libro 126 de 266. Libro 126 de 266 - Geophysical Monograph
- Tapa dura
Librería: JIM1024, WEST DES MOINES, IA, Estados Unidos de AmericaJIM1024
Contactar con el vendedorVendedor de 1 estrellasCondición: Usado - Bueno
EUR 62,21
Envío por EUR 6,78Se envía dentro de Estados Unidos de AmericaCantidad disponible: 1 disponibles
hardcover. Condición: Very Good. Library withdrawn- interior looks nearly like new- CD-ROM is included. SCI-4.
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 69,36
Gastos de envío gratisSe envía dentro de Estados Unidos de AmericaCantidad disponible: 6 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 53,73
Envío por EUR 17,59Se 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 58,10
Envío por EUR 17,59Se 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
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Librería: THE SAINT BOOKSTORE, Southport, Reino UnidoTHE SAINT BOOKSTORE
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 53,75
Envío por EUR 22,39Se 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: Pearson,, 2021
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Librería: Books in my Basket, New Delhi, IndiaBooks in my Basket
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EUR 62,24
Envío por EUR 18,00Se envía de India a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Soft cover. Condición: New. ISBN:9781617295645.
Editorial: Accademia Nazionale dei Lincei, Roma, 1974
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Librería: Libreria antiquaria Atlantis (ALAI-ILAB), Torino, TO, ItaliaLibreria antiquaria Atlantis (ALAI-ILAB)
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EUR 20,00
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Opuscolo in 8°, pp. 50. Con 16 figure nel testo. Brossura editoriale. Memorie. Classe di Scienze fisiche, matematiche e naturali. Serie VIII, Vol. XII, Fasc. 1. Copia in stato di nuovo, a fogli chiusi.
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Librería: PBShop.store UK, Fairford, GLOS, Reino UnidoPBShop.store UK
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EUR 74,70
Envío por EUR 7,93Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
HRD. Condición: New. New Book. Shipped from UK. Established seller since 2000.
Idioma: Inglés
Editorial: Manning, 2025
Serie: In Action, Libro 159 de 182. Libro 159 de 182 - In Action
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Librería: Russell Books, Victoria, BC, CanadaRussell Books
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EUR 64,91
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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.
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EUR 73,93
Envío por EUR 10,50Se envía de Irlanda a Estados Unidos de AmericaCantidad disponible: Más de 20 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
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EUR 82,44
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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 82,44
Envío por EUR 14,66Se 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 91,59
Envío por EUR 9,19Se envía dentro de Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Condición: New. 2026. 1st Edition. paperback. . . . . . Books ship from the US and Ireland.
- Tapa dura
Librería: Rarewaves.com USA, London, LONDO, Reino UnidoRarewaves.com USA
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EUR 102,66
Gastos de envío gratisSe envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Hardback. Condición: New.
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Librería: Rarewaves USA United, OSWEGO, IL, Estados Unidos de AmericaRarewaves USA United
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EUR 58,19
Envío por EUR 43,77Se envía dentro de Estados Unidos de AmericaCantidad disponible: 10 disponibles
Paperback. Condición: New. At its core, machine learning is about efficiently identifying patterns and relationships in data. Many tasks, such as finding associations among terms so you can make accurate search recommendations or locating individuals within a social network who have similar interests, are naturally expressed as…graphs. Graph-Powered Machine Learning introduces you to graph technology concepts, highlighting the role of graphs in machine learning and big data platforms. You'll get an in-depth look at techniques including data source modeling, algorithm design, link analysis, classification, and clustering. As you master the core concepts, you'll explore three end-to-end projects that illustrate architectures, best design practices, optimization approaches, and common pitfalls. Key Features · The lifecycle of a machine learning project · Three end-to-end applications · Graphs in big data platforms · Data source modeling · Natural language processing, recommendations, and relevant search · Optimization methods Readers comfortable with machine learning basics. About the technology By organizing and analyzing your data as graphs, your applications work more fluidly with graph-centric algorithms like nearest neighbor or page rank where it's important to quickly identify and exploit relevant relationships. Modern graph data stores, like Neo4j or Amazon Neptune, are readily available tools that support graph-powered machine learning. Alessandro Negro is a Chief Scientist at GraphAware. With extensive experience in software development, software architecture, and data management, he has been a speaker at many conferences, such as Java One, Oracle Open World, and Graph Connect. He holds a Ph.D. in Computer Science and has authored several publications on graph-based machine learning.
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- Edición internacional
Librería: UK BOOKS STORE, London, LONDO, Reino UnidoUK BOOKS STORE
Contactar con el vendedorVendedor de 5 estrellasEdición internacionalCondición: Nuevo
EUR 101,94
Envío por EUR 3,64Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 3 disponibles
Paperback. Condición: New. Brand New! Fast Delivery This is an International Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 6-10 days and we do have flat rate for up to 2LB. Extra shipping charges will be requ…ested if the Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.
