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Condizione: very_good. Very good condition. Light Wear.

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paperback. Condizione: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority.

Condizione: As New. Unread book in perfect condition.

Condizione: New.

Condizione: New.

Condizione: New.

Paperback. Condizione: New. This revised edition of Graph Machine Learning extends its coverage with new chapters on LLMs and temporal graph learning and updated libraries making it an essential resource for modern data scientists.

Paperback. Condizione: New. Data scientists working with network data will be able to put their knowledge to work with this practical guide to building machine learning algorithms using graph data. The book provides a hands-on approach to implementation and associated methodologies that will have you up and running and productive in no time.…

Paperback. Condizione: New. This revised edition of Graph Machine Learning extends its coverage with new chapters on LLMs and temporal graph learning and updated libraries making it an essential resource for modern data scientists.

Paperback. Condizione: New. 2nd ed. Take your Power BI reports to the next level by learning various data modeling techniques and leveraging the latest features of Power BI effectivelyGet With Your Book: PDF Copy, AI Assistant, and Next-Gen Reader FreeKey FeaturesGet an understanding of data modeling techniques using Power BI with this up-to-date guideLearn how to define the relationships between data sets to extract valuable insightsExplore best practices for data preparation and modeling and build optimal data models to solve a wide variety of real-world business challengesBook DescriptionThis book is a comprehensive guide to understanding the ins and outs of data modeling and how to create full-fledged data models using Power BI confidently.In this new, fully updated edition, you'll learn how to connect data from multiple sources, understand data, define and manage relationships between data, and shape data models to gain deep and detailed insights about your organization. As you advance through the chapters, the book will demonstrate how to prepare efficient data models in the Power Query Editor and use simpler DAX code with new data modeling features. You'll explore how to use the various data modeling and navigation techniques and perform custom calculations using the modeling features with the help of real-world examples. Finally, you'll learn how to use some new and advanced modeling features to enhance your data models to carry out a wide variety of complex tasks. Additionally, you'll learn valuable best practices and explore common data modeling complications and the solutions to supercharge the process of creating a data model in Power BI and build better-performing data models.By the end of this Power BI book, you'll have gained the skills you need to structure data coming from multiple sources in different ways to create optimized data models that support high-performing reports and data analytics.What you will learnImplement virtual tables and time intelligence functionalities in DAX to build a powerful modelIdentify Dimension and Fact tables and implement them in Power Query EditorDeal with advanced data preparation scenarios while building Star SchemaDiscover different hierarchies and their common pitfallsUnderstand complex data models and how to decrease the level of model complexity with different approachesLearn advanced data modeling techniques such as calculation groups, aggregations, incremental refresh, RLS/OLS, and moreGet well-versed with datamarts and dataflows in PowerBIWho this book is forThis MS Power BI book is for BI users, data analysts, and analysis developers who want to become well-versed with data modeling techniques to make the most of Power BI. Basic working knowledge of Power BI and the Star Schema functionality are required to help you to understand the concepts covered in this book.…

Condizione: New.

Condizione: New. In English.

Paperback. Condizione: New. 2nd ed. Take your Power BI reports to the next level by learning various data modeling techniques and leveraging the latest features of Power BI effectivelyGet With Your Book: PDF Copy, AI Assistant, and Next-Gen Reader FreeKey FeaturesGet an understanding of data modeling techniques using Power BI with this up-to-date guideLearn how to define the relationships between data sets to extract valuable insightsExplore best practices for data preparation and modeling and build optimal data models to solve a wide variety of real-world business challengesBook DescriptionThis book is a comprehensive guide to understanding the ins and outs of data modeling and how to create full-fledged data models using Power BI confidently.In this new, fully updated edition, you'll learn how to connect data from multiple sources, understand data, define and manage relationships between data, and shape data models to gain deep and detailed insights about your organization. As you advance through the chapters, the book will demonstrate how to prepare efficient data models in the Power Query Editor and use simpler DAX code with new data modeling features. You'll explore how to use the various data modeling and navigation techniques and perform custom calculations using the modeling features with the help of real-world examples. Finally, you'll learn how to use some new and advanced modeling features to enhance your data models to carry out a wide variety of complex tasks. Additionally, you'll learn valuable best practices and explore common data modeling complications and the solutions to supercharge the process of creating a data model in Power BI and build better-performing data models.By the end of this Power BI book, you'll have gained the skills you need to structure data coming from multiple sources in different ways to create optimized data models that support high-performing reports and data analytics.What you will learnImplement virtual tables and time intelligence functionalities in DAX to build a powerful modelIdentify Dimension and Fact tables and implement them in Power Query EditorDeal with advanced data preparation scenarios while building Star SchemaDiscover different hierarchies and their common pitfallsUnderstand complex data models and how to decrease the level of model complexity with different approachesLearn advanced data modeling techniques such as calculation groups, aggregations, incremental refresh, RLS/OLS, and moreGet well-versed with datamarts and dataflows in PowerBIWho this book is forThis MS Power BI book is for BI users, data analysts, and analysis developers who want to become well-versed with data modeling techniques to make the most of Power BI. Basic working knowledge of Power BI and the Star Schema functionality are required to help you to understand the concepts covered in this book.…

Condizione: As New. Unread book in perfect condition.

Paperback. Condizione: New. This revised edition of Graph Machine Learning extends its coverage with new chapters on LLMs and temporal graph learning and updated libraries making it an essential resource for modern data scientists.

Paperback. Condizione: New. 2nd ed. Take your Power BI reports to the next level by learning various data modeling techniques and leveraging the latest features of Power BI effectivelyGet With Your Book: PDF Copy, AI Assistant, and Next-Gen Reader FreeKey FeaturesGet an understanding of data modeling techniques using Power BI with this up-to-date guideLearn how to define the relationships between data sets to extract valuable insightsExplore best practices for data preparation and modeling and build optimal data models to solve a wide variety of real-world business challengesBook DescriptionThis book is a comprehensive guide to understanding the ins and outs of data modeling and how to create full-fledged data models using Power BI confidently.In this new, fully updated edition, you'll learn how to connect data from multiple sources, understand data, define and manage relationships between data, and shape data models to gain deep and detailed insights about your organization. As you advance through the chapters, the book will demonstrate how to prepare efficient data models in the Power Query Editor and use simpler DAX code with new data modeling features. You'll explore how to use the various data modeling and navigation techniques and perform custom calculations using the modeling features with the help of real-world examples. Finally, you'll learn how to use some new and advanced modeling features to enhance your data models to carry out a wide variety of complex tasks. Additionally, you'll learn valuable best practices and explore common data modeling complications and the solutions to supercharge the process of creating a data model in Power BI and build better-performing data models.By the end of this Power BI book, you'll have gained the skills you need to structure data coming from multiple sources in different ways to create optimized data models that support high-performing reports and data analytics.What you will learnImplement virtual tables and time intelligence functionalities in DAX to build a powerful modelIdentify Dimension and Fact tables and implement them in Power Query EditorDeal with advanced data preparation scenarios while building Star SchemaDiscover different hierarchies and their common pitfallsUnderstand complex data models and how to decrease the level of model complexity with different approachesLearn advanced data modeling techniques such as calculation groups, aggregations, incremental refresh, RLS/OLS, and moreGet well-versed with datamarts and dataflows in PowerBIWho this book is forThis MS Power BI book is for BI users, data analysts, and analysis developers who want to become well-versed with data modeling techniques to make the most of Power BI. Basic working knowledge of Power BI and the Star Schema functionality are required to help you to understand the concepts covered in this book.…

paperback. Condizione: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Paperback. Condizione: New. Data scientists working with network data will be able to put their knowledge to work with this practical guide to building machine learning algorithms using graph data. The book provides a hands-on approach to implementation and associated methodologies that will have you up and running and productive in no time.…

Paperback. Condizione: New. This revised edition of Graph Machine Learning extends its coverage with new chapters on LLMs and temporal graph learning and updated libraries making it an essential resource for modern data scientists.

Paperback. Condizione: New. 2nd ed. Take your Power BI reports to the next level by learning various data modeling techniques and leveraging the latest features of Power BI effectivelyGet With Your Book: PDF Copy, AI Assistant, and Next-Gen Reader FreeKey FeaturesGet an understanding of data modeling techniques using Power BI with this up-to-date guideLearn how to define the relationships between data sets to extract valuable insightsExplore best practices for data preparation and modeling and build optimal data models to solve a wide variety of real-world business challengesBook DescriptionThis book is a comprehensive guide to understanding the ins and outs of data modeling and how to create full-fledged data models using Power BI confidently.In this new, fully updated edition, you'll learn how to connect data from multiple sources, understand data, define and manage relationships between data, and shape data models to gain deep and detailed insights about your organization. As you advance through the chapters, the book will demonstrate how to prepare efficient data models in the Power Query Editor and use simpler DAX code with new data modeling features. You'll explore how to use the various data modeling and navigation techniques and perform custom calculations using the modeling features with the help of real-world examples. Finally, you'll learn how to use some new and advanced modeling features to enhance your data models to carry out a wide variety of complex tasks. Additionally, you'll learn valuable best practices and explore common data modeling complications and the solutions to supercharge the process of creating a data model in Power BI and build better-performing data models.By the end of this Power BI book, you'll have gained the skills you need to structure data coming from multiple sources in different ways to create optimized data models that support high-performing reports and data analytics.What you will learnImplement virtual tables and time intelligence functionalities in DAX to build a powerful modelIdentify Dimension and Fact tables and implement them in Power Query EditorDeal with advanced data preparation scenarios while building Star SchemaDiscover different hierarchies and their common pitfallsUnderstand complex data models and how to decrease the level of model complexity with different approachesLearn advanced data modeling techniques such as calculation groups, aggregations, incremental refresh, RLS/OLS, and moreGet well-versed with datamarts and dataflows in PowerBIWho this book is forThis MS Power BI book is for BI users, data analysts, and analysis developers who want to become well-versed with data modeling techniques to make the most of Power BI. Basic working knowledge of Power BI and the Star Schema functionality are required to help you to understand the concepts covered in this book.…

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Data scientists working with network data will be able to put their knowledge to work with this practical guide to building machine learning algorithms using graph data. The book provides a hands-on approach to implementation and associated methodologies th.…

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Build machine learning algorithms using graph data and efficiently exploit topological information within your models Key Features:Implement machine learning techniques and algorithms in graph data Identify the relationship between nodes in order to make better business decisions Apply graph-based machine learning methods to solve real-life problems Book Description: Graph Machine Learning will introduce you to a set of tools used for processing network data and leveraging the power of the relation between entities that can be used for predictive, modeling, and analytics tasks. The first chapters will introduce you to graph theory and graph machine learning, as well as the scope of their potential use. You'll then learn all you need to know about the main machine learning models for graph representation learning: their purpose, how they work, and how they can be implemented in a wide range of supervised and unsupervised learning applications. You'll build a complete machine learning pipeline, including data processing, model training, and prediction in order to exploit the full potential of graph data. After covering the basics, you'll be taken through real-world scenarios such as extracting data from social networks, text analytics, and natural language processing (NLP) using graphs and financial transaction systems on graphs. You'll also learn how to build and scale out data-driven applications for graph analytics to store, query, and process network information, and explore the latest trends on graphs. By the end of this machine learning book, you will have learned essential concepts of graph theory and all the algorithms and techniques used to build successful machine learning applications. What You Will Learn:Write Python scripts to extract features from graphs Distinguish between the main graph representation learning techniques Learn how to extract data from social networks, financial transaction systems, for text analysis, and more Implement the main unsupervised and supervised graph embedding techniques Get to grips with shallow embedding methods, graph neural networks, graph regularization methods, and more Deploy and scale out your application seamlessly Who this book is for: This book is for data scientists, data analysts, graph analysts, and graph professionals who want to leverage the information embedded in the connections and relations between data points to boost their analysis and model performance using machine learning. It will also be useful for machine learning developers or anyone who wants to build ML-driven graph databases. A beginner-level understanding of graph databases and graph data is required, alongside a solid understanding of ML basics. You'll also need intermediate-level Python programming knowledge to get started with this book.…