Graph algorithms data science de bratanic tomaz (25 resultados)
- Tapa blanda
Librería: ThriftBooks-Atlanta, AUSTELL, GA, Estados Unidos de AmericaThriftBooks-Atlanta
Contactar con el vendedorVendedor de 5 estrellasCondición: Usado - Regular
EUR 14,49
Gastos de envío gratisSe envía dentro de Estados Unidos de AmericaCantidad disponible: 1 disponibles
Paperback. Condición: Fair. No Jacket. Former library book; Readable copy. Pages may have considerable notes/highlighting. ~ ThriftBooks: Read More, Spend Less.
- Tapa blanda
Librería: INDOO, Avenel, NJ, Estados Unidos de AmericaINDOO
Contactar con el vendedorVendedor de 5 estrellasCondición: Usado - Como Nuevo
EUR 46,00
Gastos de envío gratisSe envía dentro de Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Condición: As New. Unread copy in mint condition.
- Tapa blanda
Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de AmericaPBShop.store US
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 51,56
Gastos de envío gratisSe envía dentro de Estados Unidos de AmericaCantidad disponible: 6 disponibles
PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.
- Tapa blanda
Librería: PBShop.store UK, Fairford, GLOS, Reino UnidoPBShop.store UK
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 48,24
Envío por EUR 5,82Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 6 disponibles
PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.
Más imágenes- Tapa blanda
Librería: Rarewaves.com USA, London, LONDO, Reino UnidoRarewaves.com USA
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 55,10
Gastos de envío gratisSe envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Paperback. Condición: New. Graphs are the natural way to understand connected data. This book explores the most important algorithms and techniques for graphs in data science, with practical examples and concrete advice on implementation and deployment. In Graph Algorithms for Data Science you will learn: Labeled-property gra…ph modelingConstructing a graph from structured data such as CSV or SQLNLP techniques to construct a graph from unstructured dataCypher query language syntax to manipulate data and extract insightsSocial network analysis algorithms like PageRank and community detectionHow to translate graph structure to a ML model input with node embedding modelsUsing graph features in node classification and link prediction workflows Graph Algorithms for Data Science is a hands-on guide to working with graph-based data in applications like machine learning, fraud detection, and business data analysis. It's filled with fascinating and fun projects, demonstrating the ins-and-outs of graphs. You'll gain practical skills by analyzing Twitter, building graphs with NLP techniques, and much more. You don't need any graph experience to start benefiting from this insightful guide. These powerful graph algorithms are explained in clear, jargon-free text and illustrations that makes them easy to apply to your own projects. about the technology Graphs reveal the relationships in your data. Tracking these interlinking connections reveals new insights and influences and lets you analyze each data point as part of a larger whole. This interconnected data is perfect for machine learning, as well as analyzing social networks, communities, and even product recommendations. about the book Graph Algorithms for Data Science teaches you how to construct graphs from both structured and unstructured data. You'll learn how the flexible Cypher query language can be used to easily manipulate graph structures, and extract amazing insights. The book explores common and useful graph algorithms like PageRank and community detection/clustering algorithms. Each new algorithm you learn is instantly put into action to complete a hands-on data project, including modeling a social network! Finally, you'll learn how to utilize graphs to upgrade your machine learning, including utilizing node embedding models and graph neural networks.
- Tapa blanda
Librería: Chiron Media, Wallingford, , Reino UnidoChiron Media
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 40,62
Envío por EUR 17,96Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 1 disponibles
paperback. Condición: New.
- Tapa blanda
Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de AmericaGrand Eagle Retail
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 61,28
Gastos de envío gratisSe envía dentro de Estados Unidos de AmericaCantidad disponible: 1 disponibles
Paperback. Condición: new. Paperback. Graphs are the natural way to understand connected data. This book explores the most important algorithms and techniques for graphs in data science, with practical examples and concrete advice on implementation and deployment. In Graph Algorithms for Data Science you will learn: Labeled-prop…erty graph modelingConstructing a graph from structured data such as CSV or SQLNLP techniques to construct a graph from unstructured dataCypher query language syntax to manipulate data and extract insightsSocial network analysis algorithms like PageRank and community detectionHow to translate graph structure to a ML model input with node embedding modelsUsing graph features in node classification and link prediction workflows Graph Algorithms for Data Science is a hands-on guide to working with graph-based data in applications like machine learning, fraud detection, and business data analysis. It's filled with fascinating and fun projects, demonstrating the ins-and-outs of graphs. You'll gain practical skills by analyzing Twitter, building graphs with NLP techniques, and much more. You don't need any graph experience to start benefiting from this insightful guide. These powerful graph algorithms are explained in clear, jargon-free text and illustrations that makes them easy to apply to your own projects. about the technology Graphs reveal the relationships in your data. Tracking these interlinking connections reveals new insights and influences and lets you analyze each data point as part of a larger whole. This interconnected data is perfect for machine learning, as well as analyzing social networks, communities, and even product recommendations. about the book Graph Algorithms for Data Science teaches you how to construct graphs from both structured and unstructured data. You'll learn how the flexible Cypher query language can be used to easily manipulate graph structures, and extract amazing insights. The book explores common and useful graph algorithms like PageRank and community detection/clustering algorithms. Each new algorithm you learn is instantly put into action to complete a hands-on data project, including modeling a social network! Finally, you'll learn how to utilize graphs to upgrade your machine learning, including utilizing node embedding models and graph neural networks. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
- Tapa blanda
Librería: THE SAINT BOOKSTORE, Southport, , Reino UnidoTHE SAINT BOOKSTORE
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 47,15
Envío por EUR 20,60Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Paperback / softback. Condición: New. New copy - Usually dispatched within 4 working days.
- Tapa blanda
Librería: Chiron Media, Wallingford, , Reino UnidoChiron Media
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 49,91
Envío por EUR 17,96Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 1 disponibles
paperback. Condición: New.
- Tapa blanda
Librería: Rarewaves USA, OSWEGO, IL, Estados Unidos de AmericaRarewaves USA
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 70,18
Gastos de envío gratisSe envía dentro de Estados Unidos de AmericaCantidad disponible: 1 disponibles
Paperback. Condición: New. Graphs are the natural way to understand connected data. This book explores the most important algorithms and techniques for graphs in data science, with practical examples and concrete advice on implementation and deployment. In Graph Algorithms for Data Science you will learn: Labeled-property gra…ph modelingConstructing a graph from structured data such as CSV or SQLNLP techniques to construct a graph from unstructured dataCypher query language syntax to manipulate data and extract insightsSocial network analysis algorithms like PageRank and community detectionHow to translate graph structure to a ML model input with node embedding modelsUsing graph features in node classification and link prediction workflows Graph Algorithms for Data Science is a hands-on guide to working with graph-based data in applications like machine learning, fraud detection, and business data analysis. It's filled with fascinating and fun projects, demonstrating the ins-and-outs of graphs. You'll gain practical skills by analyzing Twitter, building graphs with NLP techniques, and much more. You don't need any graph experience to start benefiting from this insightful guide. These powerful graph algorithms are explained in clear, jargon-free text and illustrations that makes them easy to apply to your own projects. about the technology Graphs reveal the relationships in your data. Tracking these interlinking connections reveals new insights and influences and lets you analyze each data point as part of a larger whole. This interconnected data is perfect for machine learning, as well as analyzing social networks, communities, and even product recommendations. about the book Graph Algorithms for Data Science teaches you how to construct graphs from both structured and unstructured data. You'll learn how the flexible Cypher query language can be used to easily manipulate graph structures, and extract amazing insights. The book explores common and useful graph algorithms like PageRank and community detection/clustering algorithms. Each new algorithm you learn is instantly put into action to complete a hands-on data project, including modeling a social network! Finally, you'll learn how to utilize graphs to upgrade your machine learning, including utilizing node embedding models and graph neural networks.
- 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 58,06
Envío por EUR 10,50Se envía de Irlanda a Estados Unidos de AmericaCantidad disponible: 2 disponibles
Condición: New. 2024. 1st Edition. paperback. . . . . .
- Tapa blanda
Librería: Ria Christie Collections, Uxbridge, Reino UnidoRia Christie Collections
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 58,37
Envío por EUR 13,89Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 2 disponibles
Condición: New. In.
- Tapa blanda
Librería: Romtrade Corp., STERLING HEIGHTS, MI, Estados Unidos de AmericaRomtrade Corp.
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 74,46
Gastos de envío gratisSe envía dentro de Estados Unidos de AmericaCantidad disponible: 1 disponibles
Condición: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
- Tapa blanda
Librería: Books Puddle, New York, NY, Estados Unidos de AmericaBooks Puddle
Contactar con el vendedorVendedor de 4 estrellasCondición: Nuevo
EUR 73,84
Envío por EUR 3,49Se envía dentro de Estados Unidos de AmericaCantidad disponible: 2 disponibles
Condición: New.
- Tapa blanda
Librería: SMASS Sellers, IRVING, TX, Estados Unidos de AmericaSMASS Sellers
Contactar con el vendedorVendedor de 4 estrellasCondición: Nuevo
EUR 77,59
Gastos de envío gratisSe envía dentro de Estados Unidos de AmericaCantidad disponible: 1 disponibles
Condición: New. Brand New Original US Edition. Customer service! Satisfaction Guaranteed.
- Tapa blanda
Librería: Majestic Books, Hounslow, , Reino UnidoMajestic Books
Contactar con el vendedorVendedor de 4 estrellasCondición: Nuevo
EUR 71,23
Envío por EUR 7,54Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 2 disponibles
Condición: New.
- Tapa blanda
Librería: Kennys Bookstore, Olney, MD, Estados Unidos de AmericaKennys Bookstore
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 71,81
Envío por EUR 9,19Se envía dentro de Estados Unidos de AmericaCantidad disponible: 2 disponibles
Condición: New. 2024. 1st Edition. paperback. . . . . . Books ship from the US and Ireland.
- Tapa blanda
Librería: Biblios, frankfurt am main, HESSE, AlemaniaBiblios
Contactar con el vendedorVendedor de 4 estrellasCondición: Nuevo
EUR 70,98
Envío por EUR 9,95Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 4 disponibles
Condición: New.
- Tapa blanda
Librería: Speedyhen, Hertfordshire, Reino UnidoSpeedyhen
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 49,42
Envío por EUR 47,53Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 2 disponibles
Condición: NEW.
- Tapa blanda
Librería: moluna, Greven, , Alemaniamoluna
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 61,17
Envío por EUR 48,99Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 2 disponibles
Condición: New. Über den AutorToma Bratani is a network scientist at heart, working at the intersection of graphs and machine learning. He has applied these graph techniques to projects in various domains including fraud detection, biomedicine, .
- Tapa blanda
Librería: Rarewaves USA United, OSWEGO, IL, Estados Unidos de AmericaRarewaves USA United
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 72,14
Envío por EUR 43,76Se envía dentro de Estados Unidos de AmericaCantidad disponible: 1 disponibles
Paperback. Condición: New. Graphs are the natural way to understand connected data. This book explores the most important algorithms and techniques for graphs in data science, with practical examples and concrete advice on implementation and deployment. In Graph Algorithms for Data Science you will learn: Labeled-property gra…ph modelingConstructing a graph from structured data such as CSV or SQLNLP techniques to construct a graph from unstructured dataCypher query language syntax to manipulate data and extract insightsSocial network analysis algorithms like PageRank and community detectionHow to translate graph structure to a ML model input with node embedding modelsUsing graph features in node classification and link prediction workflows Graph Algorithms for Data Science is a hands-on guide to working with graph-based data in applications like machine learning, fraud detection, and business data analysis. It's filled with fascinating and fun projects, demonstrating the ins-and-outs of graphs. You'll gain practical skills by analyzing Twitter, building graphs with NLP techniques, and much more. You don't need any graph experience to start benefiting from this insightful guide. These powerful graph algorithms are explained in clear, jargon-free text and illustrations that makes them easy to apply to your own projects. about the technology Graphs reveal the relationships in your data. Tracking these interlinking connections reveals new insights and influences and lets you analyze each data point as part of a larger whole. This interconnected data is perfect for machine learning, as well as analyzing social networks, communities, and even product recommendations. about the book Graph Algorithms for Data Science teaches you how to construct graphs from both structured and unstructured data. You'll learn how the flexible Cypher query language can be used to easily manipulate graph structures, and extract amazing insights. The book explores common and useful graph algorithms like PageRank and community detection/clustering algorithms. Each new algorithm you learn is instantly put into action to complete a hands-on data project, including modeling a social network! Finally, you'll learn how to utilize graphs to upgrade your machine learning, including utilizing node embedding models and graph neural networks.
- Tapa blanda
Librería: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 93,72
Envío por EUR 32,38Se envía de Australia a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Paperback. Condición: new. Paperback. Graphs are the natural way to understand connected data. This book explores the most important algorithms and techniques for graphs in data science, with practical examples and concrete advice on implementation and deployment. In Graph Algorithms for Data Science you will learn: Labeled-prop…erty graph modelingConstructing a graph from structured data such as CSV or SQLNLP techniques to construct a graph from unstructured dataCypher query language syntax to manipulate data and extract insightsSocial network analysis algorithms like PageRank and community detectionHow to translate graph structure to a ML model input with node embedding modelsUsing graph features in node classification and link prediction workflows Graph Algorithms for Data Science is a hands-on guide to working with graph-based data in applications like machine learning, fraud detection, and business data analysis. It's filled with fascinating and fun projects, demonstrating the ins-and-outs of graphs. You'll gain practical skills by analyzing Twitter, building graphs with NLP techniques, and much more. You don't need any graph experience to start benefiting from this insightful guide. These powerful graph algorithms are explained in clear, jargon-free text and illustrations that makes them easy to apply to your own projects. about the technology Graphs reveal the relationships in your data. Tracking these interlinking connections reveals new insights and influences and lets you analyze each data point as part of a larger whole. This interconnected data is perfect for machine learning, as well as analyzing social networks, communities, and even product recommendations. about the book Graph Algorithms for Data Science teaches you how to construct graphs from both structured and unstructured data. You'll learn how the flexible Cypher query language can be used to easily manipulate graph structures, and extract amazing insights. The book explores common and useful graph algorithms like PageRank and community detection/clustering algorithms. Each new algorithm you learn is instantly put into action to complete a hands-on data project, including modeling a social network! Finally, you'll learn how to utilize graphs to upgrade your machine learning, including utilizing node embedding models and graph neural networks. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
- Tapa blanda
Librería: Rarewaves.com UK, London, Reino UnidoRarewaves.com UK
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 50,93
Envío por EUR 75,35Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Paperback. Condición: New. Graphs are the natural way to understand connected data. This book explores the most important algorithms and techniques for graphs in data science, with practical examples and concrete advice on implementation and deployment. In Graph Algorithms for Data Science you will learn: Labeled-property gra…ph modelingConstructing a graph from structured data such as CSV or SQLNLP techniques to construct a graph from unstructured dataCypher query language syntax to manipulate data and extract insightsSocial network analysis algorithms like PageRank and community detectionHow to translate graph structure to a ML model input with node embedding modelsUsing graph features in node classification and link prediction workflows Graph Algorithms for Data Science is a hands-on guide to working with graph-based data in applications like machine learning, fraud detection, and business data analysis. It's filled with fascinating and fun projects, demonstrating the ins-and-outs of graphs. You'll gain practical skills by analyzing Twitter, building graphs with NLP techniques, and much more. You don't need any graph experience to start benefiting from this insightful guide. These powerful graph algorithms are explained in clear, jargon-free text and illustrations that makes them easy to apply to your own projects. about the technology Graphs reveal the relationships in your data. Tracking these interlinking connections reveals new insights and influences and lets you analyze each data point as part of a larger whole. This interconnected data is perfect for machine learning, as well as analyzing social networks, communities, and even product recommendations. about the book Graph Algorithms for Data Science teaches you how to construct graphs from both structured and unstructured data. You'll learn how the flexible Cypher query language can be used to easily manipulate graph structures, and extract amazing insights. The book explores common and useful graph algorithms like PageRank and community detection/clustering algorithms. Each new algorithm you learn is instantly put into action to complete a hands-on data project, including modeling a social network! Finally, you'll learn how to utilize graphs to upgrade your machine learning, including utilizing node embedding models and graph neural networks.
- Tapa blanda
Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 62,52
Envío por EUR 63,33Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Taschenbuch. Condición: Neu. Neuware - Practical methods for analyzing your data with graphs, revealing hidden connections and new insights.Graphs are the natural way to represent and understand connected data. This book explores the most important algorithms and techniques for graphs in data science, with concrete advice on imp…lementation and deployment. You don't need any graph experience to start benefiting from this insightful guide. These powerful graph algorithms are explained in clear, jargon-free text and illustrations that makes them easy to apply to your own projects. In Graph Algorithms for Data Science you will learn.
- Tapa blanda
Librería: preigu, Osnabrück, Alemaniapreigu
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 68,55
Envío por EUR 70,00Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Taschenbuch. Condición: Neu. Graph Algorithms for Data Science | Tomaz Bratanic | Taschenbuch | Kartoniert / Broschiert | Englisch | 2024 | Manning Publications | EAN 9781617299469 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.
