Graph powered machine learning von alessandro negro (12 Ergebnisse)
- Softcover
Anbieter: Basi6 International, Irving, TX, USABasi6 International
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 54,72
Versand gratisVersand innerhalb von USAAnzahl: 5 verfügbar
Zustand: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
- Softcover
Anbieter: Rarewaves USA, HEBRON, KY, USARarewaves USA
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 55,42
Versand gratisVersand innerhalb von USAAnzahl: 10 verfügbar
Paperback. Zustand: 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 gr…aphs. 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.
- Softcover
Anbieter: medimops, Berlin, Deutschlandmedimops
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Gebraucht - Gut
EUR 38,97
EUR 20,00 VersandVersand von Deutschland nach USAAnzahl: 1 verfügbar
Zustand: very good. Gut/Very good: Buch bzw. Schutzumschlag mit wenigen Gebrauchsspuren an Einband, Schutzumschlag oder Seiten. / Describes a book or dust jacket that does show some signs of wear on either the binding, dust jacket or pages.
- Softcover
Anbieter: PBShop.store UK, Fairford, GLOS, Vereinigtes KönigreichPBShop.store UK
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 56,92
EUR 6,86 VersandVersand von Vereinigtes Königreich nach USAAnzahl: 11 verfügbar
PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.
- Softcover
Anbieter: Grand Eagle Retail, Bensenville, IL, USAGrand Eagle Retail
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 65,33
Versand gratisVersand innerhalb von USAAnzahl: 1 verfügbar
Paperback. Zustand: 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 expr…essed 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.
Sprache: Englisch
Verlag: Pearson,, 2021
- Softcover
Anbieter: Books in my Basket, New Delhi, IndienBooks in my Basket
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 61,35
EUR 18,00 VersandVersand von Indien nach USAAnzahl: 1 verfügbar
In den WarenkorbSoft cover. Zustand: New. ISBN:9781617295645.
- Softcover
Anbieter: Rarewaves USA United, HEBRON, KY, USARarewaves USA United
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 57,39
EUR 43,15 VersandVersand innerhalb von USAAnzahl: 10 verfügbar
Paperback. Zustand: 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 gr…aphs. 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.
- Softcover
- Internationale Ausgabe
Anbieter: UK BOOKS STORE, London, LONDO, Vereinigtes KönigreichUK BOOKS STORE
Verkäufer/-in kontaktierenVerkäufer/-in mit 4 SternenInternationale AusgabeZustand: Gebraucht
EUR 102,38
Versand gratisVersand von Vereinigtes Königreich nach USAAnzahl: 3 verfügbar
Paperback. Zustand: New Books. 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…requested 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.
- Softcover
Anbieter: Studibuch, Stuttgart, DeutschlandStudibuch
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Gebraucht - Sehr gut
EUR 38,51
EUR 62,30 VersandVersand von Deutschland nach USAAnzahl: 1 verfügbar
paperback. Zustand: Sehr gut. 503 Seiten; 9781617295645.2 Gewicht in Gramm: 1.
- Softcover
Anbieter: moluna, Greven, Deutschlandmoluna
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 56,95
EUR 48,99 VersandVersand von Deutschland nach USAAnzahl: Mehr als 20 verfügbar
Zustand: New. Über den AutorAlessandro 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.
- Softcover
Anbieter: AussieBookSeller, Truganina, VIC, AustralienAussieBookSeller
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 102,32
EUR 31,93 VersandVersand von Australien nach USAAnzahl: 1 verfügbar
Paperback. Zustand: 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 expr…essed 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 our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
- Softcover
Anbieter: BUCHSERVICE / ANTIQUARIAT Lars Lutzer, Wahlstedt, DeutschlandBUCHSERVICE / ANTIQUARIAT Lars Lutzer
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Gebraucht - Gut
EUR 179,90
EUR 39,95 VersandVersand von Deutschland nach USAAnzahl: 1 verfügbar
Zustand: gut. 2021. Graph-Powered Machine Learning In englischer Sprache. pages.
