RavenDB 2.x beginner's guide

RavenDB 2.x beginner's guide PDF Author: Khaled Tannir
Publisher: Packt Publishing Ltd
ISBN: 1783283807
Category : Computers
Languages : en
Pages : 576

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Book Description
Written in a friendly, example-driven Beginner’s Guide format, there are plenty of step-by-step instructions and examples that are designed to help you get started with RavenDB. If you are a .NET developer, new to document-oriented databases, and you wish to learn how to build applications using NoSQL databases, then this book is for you. Experience with relational database systems will be helpful, but not necessary.

Optimizing Hadoop for MapReduce

Optimizing Hadoop for MapReduce PDF Author: Khaled Tannir
Publisher: Packt Publishing Ltd
ISBN: 1783285664
Category : Computers
Languages : en
Pages : 162

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Book Description
This book is an example-based tutorial that deals with Optimizing Hadoop for MapReduce job performance. If you are a Hadoop administrator, developer, MapReduce user, or beginner, this book is the best choice available if you wish to optimize your clusters and applications. Having prior knowledge of creating MapReduce applications is not necessary, but will help you better understand the concepts and snippets of MapReduce class template code.

MongoDB High Availability

MongoDB High Availability PDF Author: Afshin Mehrabani
Publisher: Packt Publishing Ltd
ISBN: 1783986735
Category : Computers
Languages : en
Pages : 239

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Book Description
This book has a perfect balance of concepts and their practical implementation along with solutions to make a highly available MongoDB server with clear instructions and guidance. If you are using MongoDB in a production environment and need a solution to make a highly available MongoDB server, this book is ideal for you. Familiarity with MongoDB is expected so that you understand the content of this book.

Practical Data Analysis Cookbook

Practical Data Analysis Cookbook PDF Author: Tomasz Drabas
Publisher: Packt Publishing Ltd
ISBN: 1783558512
Category : Computers
Languages : en
Pages : 384

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Book Description
Over 60 practical recipes on data exploration and analysis About This Book Clean dirty data, extract accurate information, and explore the relationships between variables Forecast the output of an electric plant and the water flow of American rivers using pandas, NumPy, Statsmodels, and scikit-learn Find and extract the most important features from your dataset using the most efficient Python libraries Who This Book Is For If you are a beginner or intermediate-level professional who is looking to solve your day-to-day, analytical problems with Python, this book is for you. Even with no prior programming and data analytics experience, you will be able to finish each recipe and learn while doing so. What You Will Learn Read, clean, transform, and store your data usng Pandas and OpenRefine Understand your data and explore the relationships between variables using Pandas and D3.js Explore a variety of techniques to classify and cluster outbound marketing campaign calls data of a bank using Pandas, mlpy, NumPy, and Statsmodels Reduce the dimensionality of your dataset and extract the most important features with pandas, NumPy, and mlpy Predict the output of a power plant with regression models and forecast water flow of American rivers with time series methods using pandas, NumPy, Statsmodels, and scikit-learn Explore social interactions and identify fraudulent activities with graph theory concepts using NetworkX and Gephi Scrape Internet web pages using urlib and BeautifulSoup and get to know natural language processing techniques to classify movies ratings using NLTK Study simulation techniques in an example of a gas station with agent-based modeling In Detail Data analysis is the process of systematically applying statistical and logical techniques to describe and illustrate, condense and recap, and evaluate data. Its importance has been most visible in the sector of information and communication technologies. It is an employee asset in almost all economy sectors. This book provides a rich set of independent recipes that dive into the world of data analytics and modeling using a variety of approaches, tools, and algorithms. You will learn the basics of data handling and modeling, and will build your skills gradually toward more advanced topics such as simulations, raw text processing, social interactions analysis, and more. First, you will learn some easy-to-follow practical techniques on how to read, write, clean, reformat, explore, and understand your data—arguably the most time-consuming (and the most important) tasks for any data scientist. In the second section, different independent recipes delve into intermediate topics such as classification, clustering, predicting, and more. With the help of these easy-to-follow recipes, you will also learn techniques that can easily be expanded to solve other real-life problems such as building recommendation engines or predictive models. In the third section, you will explore more advanced topics: from the field of graph theory through natural language processing, discrete choice modeling to simulations. You will also get to expand your knowledge on identifying fraud origin with the help of a graph, scrape Internet websites, and classify movies based on their reviews. By the end of this book, you will be able to efficiently use the vast array of tools that the Python environment has to offer. Style and approach This hands-on recipe guide is divided into three sections that tackle and overcome real-world data modeling problems faced by data analysts/scientist in their everyday work. Each independent recipe is written in an easy-to-follow and step-by-step fashion.

Learning Predictive Analytics with R

Learning Predictive Analytics with R PDF Author: Eric Mayor
Publisher: Packt Publishing Ltd
ISBN: 1782169369
Category : Computers
Languages : en
Pages : 333

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Book Description
Get to grips with key data visualization and predictive analytic skills using R About This Book Acquire predictive analytic skills using various tools of R Make predictions about future events by discovering valuable information from data using R Comprehensible guidelines that focus on predictive model design with real-world data Who This Book Is For If you are a statistician, chief information officer, data scientist, ML engineer, ML practitioner, quantitative analyst, and student of machine learning, this is the book for you. You should have basic knowledge of the use of R. Readers without previous experience of programming in R will also be able to use the tools in the book. What You Will Learn Customize R by installing and loading new packages Explore the structure of data using clustering algorithms Turn unstructured text into ordered data, and acquire knowledge from the data Classify your observations using Naive Bayes, k-NN, and decision trees Reduce the dimensionality of your data using principal component analysis Discover association rules using Apriori Understand how statistical distributions can help retrieve information from data using correlations, linear regression, and multilevel regression Use PMML to deploy the models generated in R In Detail R is statistical software that is used for data analysis. There are two main types of learning from data: unsupervised learning, where the structure of data is extracted automatically; and supervised learning, where a labeled part of the data is used to learn the relationship or scores in a target attribute. As important information is often hidden in a lot of data, R helps to extract that information with its many standard and cutting-edge statistical functions. This book is packed with easy-to-follow guidelines that explain the workings of the many key data mining tools of R, which are used to discover knowledge from your data. You will learn how to perform key predictive analytics tasks using R, such as train and test predictive models for classification and regression tasks, score new data sets and so on. All chapters will guide you in acquiring the skills in a practical way. Most chapters also include a theoretical introduction that will sharpen your understanding of the subject matter and invite you to go further. The book familiarizes you with the most common data mining tools of R, such as k-means, hierarchical regression, linear regression, association rules, principal component analysis, multilevel modeling, k-NN, Naive Bayes, decision trees, and text mining. It also provides a description of visualization techniques using the basic visualization tools of R as well as lattice for visualizing patterns in data organized in groups. This book is invaluable for anyone fascinated by the data mining opportunities offered by GNU R and its packages. Style and approach This is a practical book, which analyzes compelling data about life, health, and death with the help of tutorials. It offers you a useful way of interpreting the data that's specific to this book, but that can also be applied to any other data.

Modern Web Development

Modern Web Development PDF Author: Dino Esposito
Publisher: Microsoft Press
ISBN: 1509300546
Category : Computers
Languages : en
Pages : 1061

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Book Description
Master powerful new approaches to web architecture, design, and user experience This book presents a pragmatic, problem-driven, user-focused approach to planning, designing, and building dynamic web solutions. You’ll learn how to gain maximum value from Domain-Driven Design (DDD), define optimal supporting architecture, and succeed with modern UX-first design approaches. The author guides you through choosing and implementing specific technologies and addresses key user-experience topics, including mobile-friendly and responsive design. You’ll learn how to gain more value from existing Microsoft technologies such as ASP.NET MVC and SignalR by using them alongside other technologies such as Bootstrap, AJAX, JSON, and JQuery. By using these techniques and understanding the new ASP.NET Core 1.0, you can quickly build advanced web solutions that solve today’s problems and deliver an outstanding user experience. Microsoft MVP Dino Esposito shows you how to: Plan websites and web apps to mirror real-world social and business processes Use DDD to dissect and master the complexity of business domains Use UX-Driven Design to reduce costs and give customers what they want Realistically compare server-side and client-side web paradigms Get started with the new ASP.NET Core 1.0 Simplify modern visual webpage construction with Bootstrap Master practical, efficient techniques for running ASP.NET MVC projects Consider new options for implementing persistence and working with data models Understand Responsive Web Design’s pros, cons, and tradeoffs Build truly mobile-friendly, mobile-optimized websites About This Book For experienced developers and solution architects who want to plan and develop web solutions more effectively Assumes basic familiarity with the Microsoft web development stack

Graph Databases

Graph Databases PDF Author: Ian Robinson
Publisher: "O'Reilly Media, Inc."
ISBN: 1491930861
Category : Computers
Languages : en
Pages : 238

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Book Description
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

Pro C# 5.0 and the .NET 4.5 Framework

Pro C# 5.0 and the .NET 4.5 Framework PDF Author: Andrew Troelsen
Publisher: Apress
ISBN: 1430242345
Category : Computers
Languages : en
Pages : 1533

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Book Description
This new edition of Pro C# 5.0 and the .NET 4.5 Platform has been completely revised and rewritten to reflect the latest changes to the C# language specification and new advances in the .NET Framework. You'll find new chapters covering all the important new features that make .NET 4.5 the most comprehensive release yet, including: .NET APIs for Windows 8 style UI apps New asynchronous task-based model for async operations How HTML5 support is being wrapped into C# web applications New programming interfaces for HTTP applications, including improved IPv6 support Expanded WPF, WCF and WF libraries giving C# more power than ever before This comes on top of award winning coverage of core C# features, both old and new, that have made the previous editions of this book so popular (you'll find everything from generics to pLINQ covered here). The mission of this text is to provide you with a rock-solid foundation in the C# programming language and the core aspects of the .NET platform (assemblies, remoting, Windows Forms, Web Forms, ADO.NET, XML web services, etc.). Once you digest the information presented in these 25 chapters, you’ll be in a perfect position to apply this knowledge to your specific programming assignments, and you’ll be well equipped to explore the .NET universe on your own terms.

Learning Node

Learning Node PDF Author: Shelley Powers
Publisher: "O'Reilly Media, Inc."
ISBN: 1449326153
Category : Computers
Languages : en
Pages : 395

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Book Description
Take your web development skills from browser to server with Node—and learn how to write fast, highly scalable network applications on this JavaScript-based platform. With this hands-on guide, you’ll quickly master Node’s core fundamentals, gain experience with several built-in and contributed modules, and learn the differences and parallels between client- and server-side programming. Get up to speed on Node’s event-driven, asynchronous I/O model for developing data-intensive applications that are frequently accessed but computationally simple. If you’re comfortable working with JavaScript, this book provides numerous programming and deployment examples to help you take advantage of server-side development with Node. Explore Node’s unique approach to asynchronous development Build sample Node applications with the Express framework and Connect middleware Use NoSQL solutions such as Redis and MongoDB—and explore Node’s relational database modules Work with PDF files, serve HTML5 media, and create graphics with Canvas Set up bidirectional communication between browser and server with WebSockets Learn in-depth practices for debugging and testing your applications Deploy Node applications in the cloud or on your own system "Learning Node will make it easy for someone from any programming background to get a grip on Node.js and build amazing projects." —Tom Hughes-Croucher, co-author of Node: Up and Running (O’Reilly)

Patterns, Principles, and Practices of Domain-Driven Design

Patterns, Principles, and Practices of Domain-Driven Design PDF Author: Scott Millett
Publisher: John Wiley & Sons
ISBN: 1118714695
Category : Computers
Languages : en
Pages : 800

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Book Description
Methods for managing complex software construction following the practices, principles and patterns of Domain-Driven Design with code examples in C# This book presents the philosophy of Domain-Driven Design (DDD) in a down-to-earth and practical manner for experienced developers building applications for complex domains. A focus is placed on the principles and practices of decomposing a complex problem space as well as the implementation patterns and best practices for shaping a maintainable solution space. You will learn how to build effective domain models through the use of tactical patterns and how to retain their integrity by applying the strategic patterns of DDD. Full end-to-end coding examples demonstrate techniques for integrating a decomposed and distributed solution space while coding best practices and patterns advise you on how to architect applications for maintenance and scale. Offers a thorough introduction to the philosophy of DDD for professional developers Includes masses of code and examples of concept in action that other books have only covered theoretically Covers the patterns of CQRS, Messaging, REST, Event Sourcing and Event-Driven Architectures Also ideal for Java developers who want to better understand the implementation of DDD