Download or read book Neo4j Graph Data Science Certified written by Cristian Scutaru and published by Cristian Scutaru. This book was released on with total page 86 pages. Available in PDF, EPUB and Kindle. Book excerpt: Who this book is for • Anyone interested in the new Neo4j Graph Data Science Certification exam. • Data Scientists trying to pass a FREE specialty exam. • Software Developers curious to learn advanced Graph Algorithms. • Neo4j Professionals looking to acquire new skills in graph databases. • All those looking for a higher score at the free online exam. • People with not enough time for long hands-on labs and courses. This book contains two original practice tests with 40 questions each, similar to the exam questions for the Neo4j Graph Data Science free online certification • Questions are similar and close to those found in the new online exam. • This is not a brain dump, but the very similar questions will help you understand the concepts behind. • In a separate section, you get explanations for each answer, with external references, and important hints. • The real exam is very similar to each practice test here: 40 total questions, in max 60 minutes, 80% passing score. • The exact same categories as in the online exam: Library (around 20%) + Workflow (35%) + Algorithm (45%). • All Library questions are first, followed by Workflow questions, and ending up with Algorithm questions. Check also the interactive version of this book as an Udemy course, with the "Neo4j Graph Data Science Certified: Practice Exams" title.

Download or read book Graph Algorithms written by Mark Needham and published by "O'Reilly Media, Inc.". This book was released on 2019-05-16 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover how graph algorithms can help you leverage the relationships within your data to develop more intelligent solutions and enhance your machine learning models. You’ll learn how graph analytics are uniquely suited to unfold complex structures and reveal difficult-to-find patterns lurking in your data. Whether you are trying to build dynamic network models or forecast real-world behavior, this book illustrates how graph algorithms deliver value—from finding vulnerabilities and bottlenecks to detecting communities and improving machine learning predictions. This practical book walks you through hands-on examples of how to use graph algorithms in Apache Spark and Neo4j—two of the most common choices for graph analytics. Also included: sample code and tips for over 20 practical graph algorithms that cover optimal pathfinding, importance through centrality, and community detection. Learn how graph analytics vary from conventional statistical analysis Understand how classic graph algorithms work, and how they are applied Get guidance on which algorithms to use for different types of questions Explore algorithm examples with working code and sample datasets from Spark and Neo4j See how connected feature extraction can increase machine learning accuracy and precision Walk through creating an ML workflow for link prediction combining Neo4j and Spark

Download or read book Graph Data Science with Neo4j written by Estelle Scifo and published by Packt Publishing Ltd. This book was released on 2023-01-31 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: Supercharge your data with the limitless potential of Neo4j 5, the premier graph database for cutting-edge machine learning Purchase of the print or Kindle book includes a free PDF eBook Key FeaturesExtract meaningful information from graph data with Neo4j's latest version 5Use Graph Algorithms into a regular Machine Learning pipeline in PythonLearn the core principles of the Graph Data Science Library to make predictions and create data science pipelines.Book Description Neo4j, along with its Graph Data Science (GDS) library, is a complete solution to store, query, and analyze graph data. As graph databases are getting more popular among developers, data scientists are likely to face such databases in their career, making it an indispensable skill to work with graph algorithms for extracting context information and improving the overall model prediction performance. Data scientists working with Python will be able to put their knowledge to work with this practical guide to Neo4j and the GDS library that offers step-by-step explanations of essential concepts and practical instructions for implementing data science techniques on graph data using the latest Neo4j version 5 and its associated libraries. You'll start by querying Neo4j with Cypher and learn how to characterize graph datasets. As you get the hang of running graph algorithms on graph data stored into Neo4j, you'll understand the new and advanced capabilities of the GDS library that enable you to make predictions and write data science pipelines. Using the newly released GDSL Python driver, you'll be able to integrate graph algorithms into your ML pipeline. By the end of this book, you'll be able to take advantage of the relationships in your dataset to improve your current model and make other types of elaborate predictions. What you will learnUse the Cypher query language to query graph databases such as Neo4jBuild graph datasets from your own data and public knowledge graphsMake graph-specific predictions such as link predictionExplore the latest version of Neo4j to build a graph data science pipelineRun a scikit-learn prediction algorithm with graph dataTrain a predictive embedding algorithm in GDS and manage the model storeWho this book is for If you're a data scientist or data professional with a foundation in the basics of Neo4j and are now ready to understand how to build advanced analytics solutions, you'll find this graph data science book useful. Familiarity with the major components of a data science project in Python and Neo4j is necessary to follow the concepts covered in this book.

Download or read book Hands On Graph Analytics with Neo4j written by Estelle Scifo and published by Packt Publishing Ltd. This book was released on 2020-08-21 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover how to use Neo4j to identify relationships within complex and large graph datasets using graph modeling, graph algorithms, and machine learning Key FeaturesGet up and running with graph analytics with the help of real-world examplesExplore various use cases such as fraud detection, graph-based search, and recommendation systemsGet to grips with the Graph Data Science library with the help of examples, and use Neo4j in the cloud for effective application scalingBook Description Neo4j is a graph database that includes plugins to run complex graph algorithms. The book starts with an introduction to the basics of graph analytics, the Cypher query language, and graph architecture components, and helps you to understand why enterprises have started to adopt graph analytics within their organizations. You’ll find out how to implement Neo4j algorithms and techniques and explore various graph analytics methods to reveal complex relationships in your data. You’ll be able to implement graph analytics catering to different domains such as fraud detection, graph-based search, recommendation systems, social networking, and data management. You’ll also learn how to store data in graph databases and extract valuable insights from it. As you become well-versed with the techniques, you’ll discover graph machine learning in order to address simple to complex challenges using Neo4j. You will also understand how to use graph data in a machine learning model in order to make predictions based on your data. Finally, you’ll get to grips with structuring a web application for production using Neo4j. By the end of this book, you’ll not only be able to harness the power of graphs to handle a broad range of problem areas, but you’ll also have learned how to use Neo4j efficiently to identify complex relationships in your data. What you will learnBecome well-versed with Neo4j graph database building blocks, nodes, and relationshipsDiscover how to create, update, and delete nodes and relationships using Cypher queryingUse graphs to improve web search and recommendationsUnderstand graph algorithms such as pathfinding, spatial search, centrality, and community detectionFind out different steps to integrate graphs in a normal machine learning pipelineFormulate a link prediction problem in the context of machine learningImplement graph embedding algorithms such as DeepWalk, and use them in Neo4j graphsWho this book is for This book is for data analysts, business analysts, graph analysts, and database developers looking to store and process graph data to reveal key data insights. This book will also appeal to data scientists who want to build intelligent graph applications catering to different domains. Some experience with Neo4j is required.

Download or read book Neo4j Certified Professional Exam Practice Tests written by Cristian Scutaru and published by Cristian Scutaru. This book was released on 2020-12-29 with total page 181 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains two high-quality practice tests of 80 questions each - with answers and explanations - to help you pass or improve your score on the free online Neo4j Certified Professional exam. * All questions are closely emulated from those currently found in the actual exam, so you'll not waste time on anything else. * Unlike the real exam, you'll know right away what questions you missed, and what the correct answers are. * Detailed explanations with external references for any possible choice, in each practice test question. * Quiz types distributed close to 50% multi-choice + 25% multi-select + 25% True/False. * Domains distributed close to the real exam: 40% Cypher + 30% Intro + 20% Modeling + 10% Developer. * Questions will test you on Neo4j version 3.x, but explanations will have updates on deprecated features and change history. Why not just trying again and again the free online exam, until I pass? * Because starting May 2020, you can try only once a day the real online exam. * Because the high number of multi-answer questions and the gotcha tricks may give you no idea what went wrong. * Because it is time consuming and you can easily get stuck at the same low scoring mark. * Because nothing tells you where and what you failed, and next time you will likely make the same wrong choices. * Because you can hardly improve without knowing what went wrong. * Because you may want to get a better passing score anyway, as long as it appears on your issued certificate. Same e-book as LIVE practice tests on Udemy: "Neo4j Certified Professional - Practice Exams".

Download or read book Neo4j Graph Data Science Certified written by Cristian Scutaru and published by . This book was released on 2021-04 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Who this book is for-Anyone interested in the new Neo4j Graph Data Science Certification exam.-Data Scientists trying to pass a FREE specialty exam.-Software Developers curious to learn advanced Graph Algorithms.-Neo4j Professionals looking to acquire new skills in graph databases.-All those looking for a higher score at the free online exam.-People with not enough time for long hands-on labs and courses.This book contains two original practice tests with 40 questions each, similar to the exam questions for the Neo4j Graph Data Science free online certification-Questions are similar and close to those found in the new online exam.-This is not a brain dump, but the very similar questions will help you understand the concepts behind.-In a separate section, you get explanations for each answer, with external references, and important hints.-The real exam is very similar to each practice test here: 40 total questions, in max 60 minutes, 80% passing score.-The exact same categories as in the online exam: Library (around 20%) ] Workflow (35%) + Algorithm (45%).-All Library questions are first, followed by Workflow questions, and ending up with Algorithm questions.Check also the interactive version of this book as an Udemy course, with the "Neo4j Graph Data Science Certified: Practice Exams" title.

Download or read book Learning Neo4j written by Rik Van Bruggen and published by Packt Publishing Ltd. This book was released on 2014-08-25 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is for developers who want an alternative way to store and process data within their applications. No previous graph database experience is required; however, some basic database knowledge will help you understand the concepts more easily.

Download or read book Relevant Search written by John Berryman and published by Simon and Schuster. This book was released on 2016-06-19 with total page 517 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Relevant Search demystifies relevance work. Using Elasticsearch, it teaches you how to return engaging search results to your users, helping you understand and leverage the internals of Lucene-based search engines. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Users are accustomed to and expect instant, relevant search results. To achieve this, you must master the search engine. Yet for many developers, relevance ranking is mysterious or confusing. About the Book Relevant Search demystifies the subject and shows you that a search engine is a programmable relevance framework. You'll learn how to apply Elasticsearch or Solr to your business's unique ranking problems. The book demonstrates how to program relevance and how to incorporate secondary data sources, taxonomies, text analytics, and personalization. In practice, a relevance framework requires softer skills as well, such as collaborating with stakeholders to discover the right relevance requirements for your business. By the end, you'll be able to achieve a virtuous cycle of provable, measurable relevance improvements over a search product's lifetime. What's Inside Techniques for debugging relevance? Applying search engine features to real problems? Using the user interface to guide searchers? A systematic approach to relevance? A business culture focused on improving search About the Reader For developers trying to build smarter search with Elasticsearch or Solr. About the Authors Doug Turnbull is lead relevance consultant at OpenSource Connections, where he frequently speaks and blogs. John Berryman is a data engineer at Eventbrite, where he specializes in recommendations and search. Foreword author, Trey Grainger, is a director of engineering at CareerBuilder and author of Solr in Action. Table of Contents The search relevance problem Search under the hood Debugging your first relevance problem Taming tokens Basic multifield search Term-centric search Shaping the relevance function Providing relevance feedback Designing a relevance-focused search application The relevance-centered enterprise Semantic and personalized search

Download or read book Graph Databases written by Ian Robinson and published by "O'Reilly Media, Inc.". This book was released on 2013-06-10 with total page 161 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover how graph databases can help you manage and query highly connected data. With this practical book, you’ll learn how to design and implement a graph database that brings the power of graphs to bear on a broad range of problem domains. Whether you want to speed up your response to user queries or build a database that can adapt as your business evolves, this book shows you how to apply the schema-free graph model to real-world problems. Learn how different organizations are using graph databases to outperform their competitors. With this book’s data modeling, query, and code examples, you’ll quickly be able to implement your own solution. Model data with the Cypher query language and property graph model Learn best practices and common pitfalls when modeling with graphs Plan and implement a graph database solution in test-driven fashion Explore real-world examples to learn how and why organizations use a graph database Understand common patterns and components of graph database architecture Use analytical techniques and algorithms to mine graph database information

Download or read book Redis Certified Developer written by Cristian Scutaru and published by Cristian Scutaru. This book was released on with total page 146 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains two original and high-quality practice tests of 80 questions each - with answers and explanations - to help you pass the Redis Certified Developer exam. * Just like the real exam, each practice test has 80 questions, for 90 minutes, with a 72% (500/700) passing score. * Same domains as in the actual exam: General, Keys, Data Structures, Data Modeling, Debugging, Performance, Clustering. * All questions closely emulate most from the actual exam, without duplicating them. * Unlike the real exam, you'll know right away what questions you missed, and what the correct answers are. * Detailed explanations with external references for any possible choice, in each practice test question. * Just like the actual exam, all questions have four choices, and most are single-select. Same e-book as LIVE practice tests on Udemy: "Become a Redis Certified Developer: Practice Exams"

Download or read book Graph Algorithms for Data Science written by Tomaž Bratanic and published by Simon and Schuster. This book was released on 2024-02-27 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. Graph Algorithms for Data Science is a hands-on guide to working with graph-based data in applications. 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. These powerful graph algorithms are explained in clear, jargon-free text and illustrations that makes them easy to apply to your own projects.

Download or read book Couchbase Certified Java Developer written by Cristian Scutaru and published by Cristian Scutaru. This book was released on with total page 115 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains three high-quality practice tests with 40 questions each, to help you become a Couchbase Certified Java Developer. The proctored exam you must pass is maintained by Couchbase Academy. * Most questions have added answers and references, and are original. * Other questions have added answers, and are adapted from the long Couchbase Associate Java Developer Certification Course. * All questions are similar to those currently found in the actual exam. * The real exam has 40 questions, a 90 minutes time limit, 80% passing score (max 8 questions wrong). * The exam costs $50 US per trial, whether you pass or fail. * Questions are mostly either single-choice or with multiple-selections. * Categories: General, Java SDK, Queries, Data Modeling. How you should use these tests: * Try the first practice test at your own pace, and do not worry if you fail it first… * On a separate piece of paper, mark each question number with your choice. * Quit the exam anytime, if you're not patient to go over all 40 questions. * Go to the Answers and Explanations section for your test, and check all choices for each individual question. * Read the detailed Explanation for each question, and follow the links from References to learn more. * The passing score in the actual exam is 80%. * Repeat with the second and third practice tests, as all these tests cover most types of actual exam questions. * Repeat until you score at least 90% on each test. And then go for the real deal. Good luck! Same e-book as LIVE practice tests on Udemy: "Become a Couchbase Certified Java Developer: Practice Exams".

Download or read book Data Science and Big Data Analytics written by EMC Education Services and published by John Wiley & Sons. This book was released on 2014-12-19 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Science and Big Data Analytics is about harnessing the power of data for new insights. The book covers the breadth of activities and methods and tools that Data Scientists use. The content focuses on concepts, principles and practical applications that are applicable to any industry and technology environment, and the learning is supported and explained with examples that you can replicate using open-source software. This book will help you: Become a contributor on a data science team Deploy a structured lifecycle approach to data analytics problems Apply appropriate analytic techniques and tools to analyzing big data Learn how to tell a compelling story with data to drive business action Prepare for EMC Proven Professional Data Science Certification Get started discovering, analyzing, visualizing, and presenting data in a meaningful way today!

Download or read book Graph Databases written by Ian Robinson and published by "O'Reilly Media, Inc.". This book was released on 2015-06-10 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover how graph databases can help you manage and query highly connected data. With this practical book, you’ll learn how to design and implement a graph database that brings the power of graphs to bear on a broad range of problem domains. Whether you want to speed up your response to user queries or build a database that can adapt as your business evolves, this book shows you how to apply the schema-free graph model to real-world problems. This second edition includes new code samples and diagrams, using the latest Neo4j syntax, as well as information on new functionality. Learn how different organizations are using graph databases to outperform their competitors. With this book’s data modeling, query, and code examples, you’ll quickly be able to implement your own solution. Model data with the Cypher query language and property graph model Learn best practices and common pitfalls when modeling with graphs Plan and implement a graph database solution in test-driven fashion Explore real-world examples to learn how and why organizations use a graph database Understand common patterns and components of graph database architecture Use analytical techniques and algorithms to mine graph database information

Download or read book Graph Powered Machine Learning written by Alessandro Negro and published by Simon and Schuster. This book was released on 2021-10-05 with total page 494 pages. Available in PDF, EPUB and Kindle. Book excerpt: Upgrade your machine learning models with graph-based algorithms, the perfect structure for complex and interlinked data. Summary In Graph-Powered Machine Learning, you will learn: The lifecycle of a machine learning project Graphs in big data platforms Data source modeling using graphs Graph-based natural language processing, recommendations, and fraud detection techniques Graph algorithms Working with Neo4J Graph-Powered Machine Learning teaches to use graph-based algorithms and data organization strategies to develop superior machine learning applications. You’ll dive into the role of graphs in machine learning and big data platforms, and take an in-depth look at data source modeling, algorithm design, recommendations, and fraud detection. Explore end-to-end projects that illustrate architectures and help you optimize with best design practices. Author Alessandro Negro’s extensive experience shines through in every chapter, as you learn from examples and concrete scenarios based on his work with real clients! Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Identifying relationships is the foundation of machine learning. By recognizing and analyzing the connections in your data, graph-centric algorithms like K-nearest neighbor or PageRank radically improve the effectiveness of ML applications. Graph-based machine learning techniques offer a powerful new perspective for machine learning in social networking, fraud detection, natural language processing, and recommendation systems. About the book Graph-Powered Machine Learning teaches you how to exploit the natural relationships in structured and unstructured datasets using graph-oriented machine learning algorithms and tools. In this authoritative book, you’ll master the architectures and design practices of graphs, and avoid common pitfalls. Author Alessandro Negro explores examples from real-world applications that connect GraphML concepts to real world tasks. What's inside Graphs in big data platforms Recommendations, natural language processing, fraud detection Graph algorithms Working with the Neo4J graph database About the reader For readers comfortable with machine learning basics. About the author Alessandro Negro is Chief Scientist at GraphAware. He has been a speaker at many conferences, and holds a PhD in Computer Science. Table of Contents PART 1 INTRODUCTION 1 Machine learning and graphs: An introduction 2 Graph data engineering 3 Graphs in machine learning applications PART 2 RECOMMENDATIONS 4 Content-based recommendations 5 Collaborative filtering 6 Session-based recommendations 7 Context-aware and hybrid recommendations PART 3 FIGHTING FRAUD 8 Basic approaches to graph-powered fraud detection 9 Proximity-based algorithms 10 Social network analysis against fraud PART 4 TAMING TEXT WITH GRAPHS 11 Graph-based natural language processing 12 Knowledge graphs

Download or read book BEA WebLogic Workshop 8 1 Kick Start written by Sunila Srivatsan and published by Sams Publishing. This book was released on 2004 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written by leading members of BEAUs Education team, this book offers concise, practical coverage of the real-world problems Workshop can solve for J2EE developers. It includes developing page flows and JSP applications, using tag libraries, building controls, developing Web services, processing XML data, and BEAUs new XML Beans classes, handling security, and deploying applications to production.336 pp.

Download or read book Big Data Analytics with Java written by Rajat Mehta and published by Packt Publishing Ltd. This book was released on 2017-07-31 with total page 419 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn the basics of analytics on big data using Java, machine learning and other big data tools About This Book Acquire real-world set of tools for building enterprise level data science applications Surpasses the barrier of other languages in data science and learn create useful object-oriented codes Extensive use of Java compliant big data tools like apache spark, Hadoop, etc. Who This Book Is For This book is for Java developers who are looking to perform data analysis in production environment. Those who wish to implement data analysis in their Big data applications will find this book helpful. What You Will Learn Start from simple analytic tasks on big data Get into more complex tasks with predictive analytics on big data using machine learning Learn real time analytic tasks Understand the concepts with examples and case studies Prepare and refine data for analysis Create charts in order to understand the data See various real-world datasets In Detail This book covers case studies such as sentiment analysis on a tweet dataset, recommendations on a movielens dataset, customer segmentation on an ecommerce dataset, and graph analysis on actual flights dataset. This book is an end-to-end guide to implement analytics on big data with Java. Java is the de facto language for major big data environments, including Hadoop. This book will teach you how to perform analytics on big data with production-friendly Java. This book basically divided into two sections. The first part is an introduction that will help the readers get acquainted with big data environments, whereas the second part will contain a hardcore discussion on all the concepts in analytics on big data. It will take you from data analysis and data visualization to the core concepts and advantages of machine learning, real-life usage of regression and classification using Naive Bayes, a deep discussion on the concepts of clustering,and a review of simple neural networks on big data using deepLearning4j or plain Java Spark code. This book is a must-have book for Java developers who want to start learning big data analytics and want to use it in the real world. Style and approach The approach of book is to deliver practical learning modules in manageable content. Each chapter is a self-contained unit of a concept in big data analytics. Book will step by step builds the competency in the area of big data analytics. Examples using real world case studies to give ideas of real applications and how to use the techniques mentioned. The examples and case studies will be shown using both theory and code.