Take charge of SaltStack to automate and configure your enterprise-grade environments About This Book Automate tasks effectively and take charge of your infrastructure Effectively scale Salt to manage thousands of machines and tackle everyday problems Explore Salt’s inner workings and advance your knowledge of it Who This Book Is For This book is ideal for IT professionals and ops engineers who already manage groups of servers, but would like to expand their knowledge and gain expertise with SaltStack. This book explains the advanced features and concepts of Salt. A basic knowledge of Salt is required in order to get to grips with advanced Salt features. What You Will Learn Automate tasks effectively, so that your infrastructure can run itself Start building more complex concepts Master user-level internals Build scaling strategies Explore monitoring strategies Learn how to troubleshoot Salt and its subcomponents Explore best practices for Salt In Detail SaltStack is a powerful configuration management and automation suite designed to manage servers and tens of thousands of nodes. This book showcases Salt as a very powerful automation framework. We will review the fundamental concepts to get you in the right frame of mind, and then explore Salt in much greater depth. You will explore Salt SSH as a powerful tool and take Salt Cloud to the next level. Next, you’ll master using Salt services with ease in your infrastructure. You will discover methods and strategies to scale your infrastructure properly. You will also learn how to use Salt as a powerful monitoring tool. By the end of this book, you will have learned troubleshooting tips and best practices to make the entire process of using Salt pain-free and easy. Style and approach This book follows a step-by-step conversational tone. Topics are covered in detail through examples and a user-friendly approach.

Unleash the power and flexibility of the Bayesian framework About This Book Simplify the Bayes process for solving complex statistical problems using Python; Tutorial guide that will take the you through the journey of Bayesian analysis with the help of sample problems and practice exercises; Learn how and when to use Bayesian analysis in your applications with this guide. Who This Book Is For Students, researchers and data scientists who wish to learn Bayesian data analysis with Python and implement probabilistic models in their day to day projects. Programming experience with Python is essential. No previous statistical knowledge is assumed. What You Will Learn Understand the essentials Bayesian concepts from a practical point of view Learn how to build probabilistic models using the Python library PyMC3 Acquire the skills to sanity-check your models and modify them if necessary Add structure to your models and get the advantages of hierarchical models Find out how different models can be used to answer different data analysis questions When in doubt, learn to choose between alternative models. Predict continuous target outcomes using regression analysis or assign classes using logistic and softmax regression. Learn how to think probabilistically and unleash the power and flexibility of the Bayesian framework In Detail The purpose of this book is to teach the main concepts of Bayesian data analysis. We will learn how to effectively use PyMC3, a Python library for probabilistic programming, to perform Bayesian parameter estimation, to check models and validate them. This book begins presenting the key concepts of the Bayesian framework and the main advantages of this approach from a practical point of view. Moving on, we will explore the power and flexibility of generalized linear models and how to adapt them to a wide array of problems, including regression and classification. We will also look into mixture models and clustering data, and we will finish with advanced topics like non-parametrics models and Gaussian processes. With the help of Python and PyMC3 you will learn to implement, check and expand Bayesian models to solve data analysis problems. Style and approach Bayes algorithms are widely used in statistics, machine learning, artificial intelligence, and data mining. This will be a practical guide allowing the readers to use Bayesian methods for statistical modelling and analysis using Python.

Get acquainted with the world of LXC About This Book Get the most practical and up-to-date resource on LXC and take full advantage of what Linux containers can offer in the day-to-day operations of large-scale applications Learn how to deploy and administer various workloads such as web applications inside LXC Save your organization time and money by building robust and secure containers and by speeding the deployment process of your software Who This Book Is For This book is for Linux engineers and software developers who are looking to deploy applications in a fast, secure, and scalable way for use in testing and production. What You Will Learn Deep dive into the foundations of Linux containers with kernel namespaces and cgroups Install, configure, and administer Linux containers with LXC and libvirt Begin writing applications using Python libvirt bindings Take an in-depth look at container networking Set up monitoring and security with LXC Build and deploy a highly available application with LXC in the cloud In Detail In recent years, containers have gained wide adoption by businesses running a variety of application loads. This became possible largely due to the advent of kernel namespaces and better resource management with control groups (cgroups). Linux containers (LXC) are a direct implementation of those kernel features that provide operating system level virtualization without the overhead of a hypervisor layer. This book starts by introducing the foundational concepts behind the implementation of LXC, then moves into the practical aspects of installing and configuring LXC containers. Moving on, you will explore container networking, security, and backups. You will also learn how to deploy LXC with technologies like Open Stack and Vagrant. By the end of the book, you will have a solid grasp of how LXC is implemented and how to run production applications in a highly available and scalable way. Style and approach A practical guide that introduces the core technologies behind Linux containers and provides a deep dive into installation, configuration, and operations of LXC.

Build effective applications by applying Odoo development best practices About This Book Each recipe stands by itself as much as possible, so that you can jump straight into the topics you prefer The recipes included cover all the major development areas of Odoo and the most important techniques explained through real-life projects From seasoned authors, learn the tricks of becoming a productive developer with the Odoo framework Who This Book Is For If you are a Python developer who wants to learn or consolidate your Odoo development skills, then this book is for you! Some experience with the JavaScript programming language and web development is required to fully benefit from the front-end chapters. What You Will Learn Install and manage Odoo environments and instances Use Models to define your application's data structures Add business logic to your applications Implement automated tests and debug Odoo apps Use back-end views to create a user interface Get to know about the access security model and internationalization features Develop front-end website features Extend the web client with new widgets and features In Detail Odoo is a full-featured open source ERP with a focus on extensibility. The flexibility and sustainability of open source is also a key selling point of Odoo. It is built on a powerful framework for rapid application development, both for back-end applications and front-end websites. The book starts by covering Odoo installation and administration, and provides a gentle introduction to application development. It then dives deep into several of the areas that an experienced developer will need to use. You’ll learn implement business logic, adapt the UI, and extend existing features. Style and Approach These practical and easy-to-follow recipes are presented step-by-step, with dozens of hands-on recipes to boost your Odoo skills. This book can also be used as a reference guide for your daily work.

Attain expert-level proficiency with Git for enhanced productivity and efficient collaboration by mastering advanced distributed version control features About This Book Set up Git for solo and collaborative development Harness the full power of Git version control system to customize Git behavior, manipulate history, integrate external tools and explore platform shortcuts A detailed guide, which explains how to apply advanced Git techniques and workflows and ways to handle submodules Who This Book Is For If you are a Git user with reasonable knowledge of Git and familiarity with basic concepts such as branching, merging, staging, and workflows, this is the book for you. Basic knowledge of installing Git and software configuration management concepts is essential. What You Will Learn Explore project history, find revisions using different criteria, and filter and format how history looks Manage your working directory and staging area for commits and interactively create new revisions and amend them Set up repositories and branches for collaboration Submit your own contributions and integrate contributions from other developers via merging or rebasing Customize Git behavior system-wide, on a per-user, per-repository, and per-file basis Take up the administration and set up of Git repositories, configure access, find and recover from repository errors, and perform repository maintenance Chose a workflow and configure and set up support for the chosen workflow In Detail Git is one of the most popular types of Source Code Management (SCM) and Distributed Version Control System (DVCS). Despite the powerful and versatile nature of the tool enveloping strong support for nonlinear development and the ability to handle large projects efficiently, it is a complex tool and often regarded as “user-unfriendly”. Getting to know the ideas and concepts behind the architecture of Git will help you make full use of its power and understand its behavior. Learning the best practices and recommended workflows should help you to avoid problems and ensure trouble-free development. The book scope is meticulously designed to help you gain deeper insights into Git's architecture, its underlying concepts, behavior, and best practices. Mastering Git starts with a quick implementation example of using Git for a collaborative development of a sample project to establish the foundation knowledge of Git operational tasks and concepts. Furthermore, as you progress through the book, the tutorials provide detailed de*ions of various areas of usage: from archaeology, through managing your own work, to working with other developers. This book also helps augment your understanding to examine and explore project history, create and manage your contributions, set up repositories and branches for collaboration in centralized and distributed version control, integrate work from other developers, customize and extend Git, and recover from repository errors. By exploring advanced Git practices, you will attain a deeper understanding of Git’s behavior, allowing you to customize and extend existing recipes and write your own. Style and approach Step-by-step instructions and useful information make this book the ultimate guide to understanding and mastering Git. This book will show road to mastery example by example, while explaining mental model of Git. The Introduction section covers the 'Essentials' just for refreshing the basics. The main highlight is that the concepts are based on HOW the technology/framework works and not just practical 'WHAT to do'.

Over 70 recipes to get you writing powerful and efficient multithreaded, asynchronous, and parallel programs in C# 6.0 About This Book Rewritten and updated to take advantage of the latest C# 6 features Learn about multithreaded, asynchronous, and parallel programming through hands-on, code-first examples Use these recipes to build fast, scalable, and reliable applications in C# Who This Book Is For This book is aimed at those who are new to multithreaded programming, and who are looking for a quick and easy way to get started. It is assumed that you have some experience in C# and .NET already, and you should also be familiar with basic computer science terminology and basic algorithms and data structures. What You Will Learn Use C# 6.0 asynchronous language features Work with raw threads, synchronize threads, and coordinate their work Develop your own asynchronous API with Task Parallel Library Work effectively with a thread pool Scale up your server application with I/O threads Parallelize your LINQ queries with PLINQ Use common concurrent collections Apply different parallel programming patterns Use Reactive Extensions to run asynchronous operations and manage their options In Detail Multi-core processors are synonymous with computing speed and power in today’s world, which is why multithreading has become a key concern for C# developers. Multithreaded code helps you create effective, scalable, and responsive applications. This is an easy-to-follow guide that will show you difficult programming problems in context. You will learn how to solve them with practical, hands-on, recipes. With these recipes, you’ll be able to start creating your own scalable and reliable multithreaded applications. Starting from learning what a thread is, we guide you through the basics and then move on to more advanced concepts such as task parallel libraries, C# asynchronous functions, and much more. Rewritten to the latest C# specification, C# 6, and updated with new and modern recipes to help you make the most of the hardware you have available, this book will help you push the boundaries of what you thought possible in C#. Style and approach This is an easy-to-follow guide full of hands-on examples of real-world multithreading tasks. Each topic is explained and placed in context, and for the more inquisitive, there are also more in-depth details of the concepts used.

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.

Discover how to rapidly prototype SEO-friendly web applications with Angular Universal About This Book : ? Rapidly build an application that's optimized for search performance ? Develop service workers to make your application truly progressive ? Automatically update metadata and load in content from external APIs Who This Book Is For : This book is ideal for experienced front-end developers who are looking to quickly work through an intelligent example that demonstrates all the key features of server-side development with Angular. You'll need some prior exposure to Angular, as we skim over the basics and get straight to work. What You Will Learn : ? Use the official tools provided by Angular to build an SEO-friendly application ? Create a dynamic web application that maps to current Angular best practices ? Manage your Angular applications with Angular CLI ? Implement server-side rendering for your future web application projects ? Configure service workers to automatically update your application in the background In Detail : Equip yourself with the skills required to create modern, progressive web applications that load quickly and efficiently. This fast-paced guide to server-side Angular leads you through an example application that uses Angular Universal to render application pages on the server, rather than the client. You'll learn how to serve your users views that load instantly, while reaping all the SEO benefits of improved page indexing. With differences of just 200 milliseconds in performance having a measurable impact on your users, it's more important than ever to get server-side right. Style and approach : With this book, you'll be equipped to create modern, SEO-friendly web apps with best practices using Angular CLI. This book focuses on creating a progressive web app using Angular that is optimized for search engines.

Learn how to build, test, secure, deploy, and efficiently consume services across distributed systems. About This Book ? Explore the wealth of options provided by Spring Cloud for wiring service dependencies in microservice systems. ? Create microservices utilizing Spring Cloud's Netflix OSS ? Architect your cloud-native data using Spring Cloud. Who This Book Is For This book appeals to developers keen to take advantage of Spring cloud, an open source library which helps developers quickly build distributed systems. Knowledge of Java and Spring Framework will be helpful, but no prior exposure to Spring Cloud is required. What You Will Learn ? Abstract Spring Cloud's feature set ? Create microservices utilizing Spring Cloud's Netflix OSS ? Create synchronous API microservices based on a message-driven architecture. ? Explore advanced topics such as distributed tracing, security, and contract testing. ? Manage and deploy applications on the production environment In Detail Developing, deploying, and operating cloud applications should be as easy as local applications. This should be the governing principle behind any cloud platform, library, or tool. Spring Cloud–an open-source library–makes it easy to develop JVM applications for the cloud. In this book, you will be introduced to Spring Cloud and will master its features from the application developer's point of view. This book begins by introducing you to microservices for Spring and the available feature set in Spring Cloud. You will learn to configure the Spring Cloud server and run the Eureka server to enable service registration and discovery. Then you will learn about techniques related to load balancing and circuit breaking and utilize all features of the Feign client. The book now delves into advanced topics where you will learn to implement distributed tracing solutions for Spring Cloud and build message-driven microservice architectures. Before running an application on Docker container s, you will master testing and securing techniques with Spring Cloud. Style and approach This comprehensive guide covers the advanced features of Spring Cloud and communicates them through a practical approach to explore the underlying concepts of how, when, and why to use them.

Getting started with data science doesn't have to be an uphill battle. This step-by-step guide is ideal for beginners who know a little Python and are looking for a quick, fast-paced introduction. About This Book ? Get up and running with the Jupyter ecosystem and some example datasets ? Learn about key machine learning concepts like SVM, KNN classifiers and Random Forests ? Discover how you can use web scraping to gather and parse your own bespoke datasets Who This Book Is For This book is ideal for professionals with a variety of job descriptions across large range of industries, given the rising popularity and accessibility of data science. You'll need some prior experience with Python, with any prior work with libraries like Pandas, Matplotlib and Pandas providing you a useful head start. What You Will Learn ? Identify potential areas of investigation and perform exploratory data analysis ? Plan a machine learning classification strategy and train classification models ? Use validation curves and dimensionality reduction to tune and enhance your models ? Scrape tabular data from web pages and transform it into Pandas DataFrames ? Create interactive, web-friendly visualizations to clearly communicate your findings In Detail Get to grips with the skills you need for entry-level data science in this hands-on Python and Jupyter course. You'll learn about some of the most commonly used libraries that are part of the Anaconda distribution, and then explore machine learning models with real datasets to give you the skills and exposure you need for the real world. We'll finish up by showing you how easy it can be to scrape and gather your own data from the open web, so that you can apply your new skills in an actionable context. Style and approach This book covers every aspect of the standard data-workflow process within a day, along with theory, practical hands-on coding, and relatable illustrations.

A hands-on guide to creating, monitoring, and tuning a high performance Spring web application About This Book ? Understand common performance pitfalls and improve your application's performance ? Build and deploy strategies for complex applications using the microservice architecture ? Understand internals of JVM - the core of all Java Runtime Environments Who This Book Is For If you’re a Spring developer who’d like to build high performance applications and have more control over your application's performance in production and development, this book is for you. Some familiarity with Java, Maven, and Eclipse is necessary. What You Will Learn ? Master programming best practices and performance improvement with bean wiring ? Analyze the performance of various AOP implementations ? Explore database interactions with Spring to optimize design and configuration ? Solve Hibernate performance issues and traps ? Leverage multithreading and concurrent programming to improve application performance ? Gain a solid foundation in JVM performance tuning using various tools ? Learn the key concepts of the microservice architecture and how to monitor them ? Perform Spring Boot performance tuning, monitoring, and health checks In Detail While writing an application, performance is paramount. Performance tuning for real-world applications often involves activities geared toward detecting bottlenecks. The recent release of Spring 5.0 brings major advancements in the rich API provided by the Spring framework, which means developers need to master its tools and techniques to achieve high performance applications. Hands-On High Performance with Spring 5 begins with the Spring framework's core features, exploring the integration of different Spring projects. It proceeds to evaluate various Spring specifications to identify those adversely affecting performance. You will learn about bean wiring configurations, aspect-oriented programming, database interaction, and Hibernate to focus on the metrics that help identify performance bottlenecks. You will also look at application monitoring, performance optimization, JVM internals, and garbage collection optimization. Lastly, the book will show you how to leverage the microservice architecture to build a high performance and resilient application. By the end of the book, you will have gained an insight into various techniques and solutions to build and troubleshoot high performance Spring-based applications. Style and approach This book takes a step-by-step approach with focused examples to teach you how to increase application performance.

A comprehensive guide to making machine data accessible across the organization using advanced dashboards About This Book ? Enrich machine-generated data and transform it into useful, meaningful insights ? Perform search operations and configurations, build dashboards, and manage logs ? Extend Splunk services with scripts and advanced configurations to process optimal results Who This Book Is For This book is intended for data analysts, business analysts, and IT administrators who want to make the best use of big data, operational intelligence, log management, and monitoring within their organization. Some knowledge of Splunk services will help you get the most out of the book What You Will Learn ? Focus on the new features of the latest version of Splunk Enterprise 7 ? Master the new offerings in Splunk: Splunk Cloud and the Machine Learning Toolkit ? Create efficient and effective searches within the organization ? Master the use of Splunk tables, charts, and graph enhancements ? Use Splunk data models and pivots with faster data model acceleration ? Master all aspects of Splunk XML dashboards with hands-on applications ? Create and deploy advanced Splunk dashboards to share valuable business insights with peers In Detail Splunk is the leading platform that fosters an efficient methodology and delivers ways to search, monitor, and analyze growing amounts of big data. This book will allow you to implement new services and utilize them to quickly and efficiently process machine-generated big data. We introduce you to all the new features, improvements, and offerings of Splunk 7. We cover the new modules of Splunk: Splunk Cloud and the Machine Learning Toolkit to ease data usage. Furthermore, you will learn to use search terms effectively with Boolean and grouping operators. You will learn not only how to modify your search to make your searches fast but also how to use wildcards efficiently. Later you will learn how to use stats to aggregate values, a chart to turn data, and a time chart to show values over time; you'll also work with fields and chart enhancements and learn how to create a data model with faster data model acceleration. Once this is done, you will learn about XML Dashboards, working with apps, building advanced dashboards, configuring and extending Splunk, advanced deployments, and more. Finally, we teach you how to use the Machine Learning Toolkit and best practices and tips to help you implement Splunk services effectively and efficiently. By the end of this book, you will have learned about the Splunk software as a whole and implemented Splunk services in your tasks at projects Style and approach An easy-to-follow, step-by-step guide to help you get to grips with real-world applications of Splunk 7.

Develop your first interactive 2D and 3D platformer game by learning the fundamentals of C# About This Book ? This is a step-by-step guide to learn the fundamentals of C# 7 *ing to develop GameObjects and master the basics of the new UI system in Unity ? Build and develop your 2D game right from scratch while implementing the principles of object-oriented programming and coding in C# 7 ? Get to grips with the fundamentals of optimizing your game using the latest features of Unity 2017 Who This Book Is For The book is targeted at beginner level Unity developers with no programming experience. If you are a Unity developer and you wish to learn how to write C# *s and code by creating games, then this book is for you. What You Will Learn ? Learn C# 7 using new features like tuples, variables, and non-nullable reference types while building games ? Understand the fundamentals of variables, methods, and code syntax in C# ? Use loops and collections efficiently in Unity to reduce the amount of code ? Develop a game using the object-oriented programming principles ? Implement simple enemy characters into the game to learn point to point movement and Tree behaviors ? Avoid performance mistakes by implementing different optimization techniques ? Export 3D models and 3D animations and import them inside a Unity project ? With your new knowledge of coding, you will be able to look at Unity's Scripting Reference code examples with confidence In Detail With the latest version of Unity 2017 released, are you interested in developing creative and interactive games while learning C# alongside? Then this is the book that you are looking for. Its all about offering you a fun introduction to the world of game programming with C#. You’ll start with the basics to get started with C# 7 and its latest features. Then you’ll see how to use C# 7 and its latest functional programming capabilities to create amazing games with Unity 2017. You’ll create your first C# * for Unity, add objects into it, and learn how to create game elements with them. Then you’ll work with the latest functional programming features of C# and how to leverage them for great game *ing. Throughout the book, you’ll learn to use the new Unity 2017 2D tool set and create an interactive 2D game with it. You will make enemies appear to challenge your player, and go through some optimization techniques to ensure great game performance. At the end, your 2D game will be transformed into 3D, and you’ll be able to skill up to become a pro C# programmer with Unity 2017! Style and approach The book takes a practical, step-by-step approach where you learn C# coding while developing fun and interactive games.

This step-by-step guide demonstrates how to build simple-to-advanced applications through examples in R using modern tools. About This Book ? Get a firm hold on the fundamentals of R through practical hands-on examples ? Get started with good R programming fundamentals for data science ? Exploit the different libraries of R to build interesting applications in R Who This Book Is For This books is for aspiring data science professionals or statisticians who would like to learn about the R programming language in a practical manner. Basic programming knowledge is assumed. What You Will Learn ? Discover techniques to leverage R’s features, and work with packages ? Perform a de*ive analysis and work with statistical models using R ? Work efficiently with objects without using loops ? Create diverse visualizations to gain better understanding of the data ? Understand ways to produce good visualizations and create reports for the results ? Read and write data from relational databases and REST APIs, both packaged and unpackaged ? Improve performance by writing better code, delegating that code to a more efficient programming language, or making it parallel In Detail R is a high-level statistical language and is widely used among statisticians and data miners to develop analytical applications. Often, data analysis people with great analytical skills lack solid programming knowledge and are unfamiliar with the correct ways to use R. Based on the version 3.4, this book will help you develop strong fundamentals when working with R by taking you through a series of full representative examples, giving you a holistic view of R. We begin with the basic installation and configuration of the R environment. As you progress through the exercises, you'll become thoroughly acquainted with R's features and its packages. With this book, you will learn about the basic concepts of R programming, work efficiently with graphs, create publication-ready and interactive 3D graphs, and gain a better understanding of the data at hand. The detailed step-by-step instructions will enable you to get a clean set of data, produce good visualizations, and create reports for the results. It also teaches you various methods to perform code profiling and performance enhancement with good programming practices, delegation, and parallelization. By the end of this book, you will know how to efficiently work with data, create quality visualizations and reports, and develop code that is modular, expressive, and maintainable. Style and Approach This is an easy-to-understand guide filled with real-world examples, giving you a holistic view of R and practical, hands-on experience.

Learn the fundamentals of vue.js by creating complex SPAs with Vuex, vue-router and more About This Book ? We bridge the gap between "learning" and "doing" by providing real-world examples that will improve your web development skills with Vue.js ? Explore the exciting features of Vue.js 2 through practical and interesting examples ? Explore modern development tools and learn how to utilize them by building applications with Vue.js Who This Book Is For This book is for developers who know the basics of JavaScript and are looking to learn Vue.js with real examples. You should understand the basics of JavaScript functions and variables and be comfortable with using CSS or a CSS framework for styling your projects. What You Will Learn ? Looping through data with Vue.js ? Searching and filtering data ? Using components to display data ? Getting a list of files using the dropbox API ? Navigating through a file tree and loading folders from a URL ? Caching with Vuex ? Pre-caching for faster navigation ? Introducing vue-router and loading components ? Using vue-router dynamic routes to load data ? Using vue-router and Vuex to create an ecommerce store In Detail Vue.js is a frontend web framework which makes it easy to do just about anything, from displaying data up to creating full-blown web apps, and has become a leading tool for web developers. This book puts Vue.js into a real-world context, guiding you through example projects that helps you build Vue.js applications from scratch. With this book, you will learn how to use Vue.js by creating three Single Page web applications. Throughout this book, we will cover the usage of Vue, for building web interfaces, Vuex, an official Vue plugin which makes caching and storing data easier, and Vue-router, a plugin for creating routes and URLs for your application. Starting with a JSON dataset, the first part of the book covers Vue objects and how to utilize each one. This will be covered by exploring different ways of displaying data from a JSON dataset. We will then move on to manipulating the data with filters and search and creating dynamic values. Next, you will see how easy it is to integrate remote data into an application by learning how to use the Dropbox API to display your Dropbox contents in an application In the final section, you will see how to build a product catalog and dynamic shopping cart using the Vue-router, giving you the building blocks of an e-commerce store. Style and approach This book takes you three projects, with step-by-step instructions to help you understand the concepts of Vue and put it into practice.

Learn and implement various Quantitative Finance concepts using the popular Python libraries About This Book ? Understand the fundamentals of Python data structures and work with time-series data ? Implement key concepts in quantitative finance using popular Python libraries such as NumPy, SciPy, and matplotlib ? A step-by-step tutorial packed with many Python programs that will help you learn how to apply Python to finance Who This Book Is For This book assumes that the readers have some basic knowledge related to Python. However, he/she has no knowledge of quantitative finance. In addition, he/she has no knowledge about financial data. What You Will Learn ? Become acquainted with Python in the first two chapters ? Run CAPM, Fama-French 3-factor, and Fama-French-Carhart 4-factor models ? Learn how to price a call, put, and several exotic options ? Understand Monte Carlo simulation, how to write a Python program to replicate the Black-Scholes-Merton options model, and how to price a few exotic options ? Understand the concept of volatility and how to test the hypothesis that volatility changes over the years ? Understand the ARCH and GARCH processes and how to write related Python programs In Detail This book uses Python as its computational tool. Since Python is free, any school or organization can download and use it. This book is organized according to various finance subjects. In other words, the first edition focuses more on Python, while the second edition is truly trying to apply Python to finance. The book starts by explaining topics exclusively related to Python. Then we deal with critical parts of Python, explaining concepts such as time value of money stock and bond evaluations, capital asset pricing model, multi-factor models, time series analysis, portfolio theory, options and futures. This book will help us to learn or review the basics of quantitative finance and apply Python to solve various problems, such as estimating IBM’s market risk, running a Fama-French 3-factor, 5-factor, or Fama-French-Carhart 4 factor model, estimating the VaR of a 5-stock portfolio, estimating the optimal portfolio, and constructing the efficient frontier for a 20-stock portfolio with real-world stock, and with Monte Carlo Simulation. Later, we will also learn how to replicate the famous Black-Scholes-Merton option model and how to price exotic options such as the average price call option. Style and approach This book takes a step-by-step approach in explaining the libraries and modules in Python, and how they can be used to implement various aspects of quantitative finance. Each concept is explained in depth and supplemented with code examples for better understanding.

Master the intricacies of Apache Storm and develop real-time stream processing applications with ease About This Book ? Exploit the various real-time processing functionalities offered by Apache Storm such as parallelism, data partitioning, and more ? Integrate Storm with other Big Data technologies like Hadoop, HBase, and Apache Kafka ? An easy-to-understand guide to effortlessly create distributed applications with Storm Who This Book Is For If you are a Java developer who wants to enter into the world of real-time stream processing applications using Apache Storm, then this book is for you. No previous experience in Storm is required as this book starts from the basics. After finishing this book, you will be able to develop not-so-complex Storm applications. What You Will Learn ? Understand the core concepts of Apache Storm and real-time processing ? Follow the steps to deploy multiple nodes of Storm Cluster ? Create Trident topologies to support various message-processing semantics ? Make your cluster sharing effective using Storm scheduling ? Integrate Apache Storm with other Big Data technologies such as Hadoop, HBase, Kafka, and more ? Monitor the health of your Storm cluster In Detail Apache Storm is a real-time Big Data processing framework that processes large amounts of data reliably, guaranteeing that every message will be processed. Storm allows you to scale your data as it grows, making it an excellent platform to solve your big data problems. This extensive guide will help you understand right from the basics to the advanced topics of Storm. The book begins with a detailed introduction to real-time processing and where Storm fits in to solve these problems. You’ll get an understanding of deploying Storm on clusters by writing a basic Storm Hello World example. Next we’ll introduce you to Trident and you’ll get a clear understanding of how you can develop and deploy a trident topology. We cover topics such as monitoring, Storm Parallelism, scheduler and log processing, in a very easy to understand manner. You will also learn how to integrate Storm with other well-known Big Data technologies such as HBase, Redis, Kafka, and Hadoop to realize the full potential of Storm. With real-world examples and clear explanations, this book will ensure you will have a thorough mastery of Apache Storm. You will be able to use this knowledge to develop efficient, distributed real-time applications to cater to your business needs. Style and approach This easy-to-follow guide is full of examples and real-world applications to help you get an in-depth understanding of Apache Storm. This book covers the basics thoroughly and also delves into the intermediate and slightly advanced concepts of application development with Apache Storm.

Discover practical solutions for a wide range of real-world network programming tasks About This Book ? Solve real-world tasks in the area of network programming, system/networking administration, network monitoring, and more. ? Familiarize yourself with the fundamentals and functionalities of SDN ? Improve your skills to become the next-gen network engineer by learning the various facets of Python programming Who This Book Is For This book is for network engineers, system/network administrators, network programmers, and even web application developers who want to solve everyday network-related problems. If you are a novice, you will develop an understanding of the concepts as you progress with this book. What You Will Learn ? Develop TCP/IP networking client/server applications ? Administer local machines' IPv4/IPv6 network interfaces ? Write multi-purpose efficient web clients for HTTP and HTTPS protocols ? Perform remote system administration tasks over Telnet and SSH connections ? Interact with popular websites via web services such as XML-RPC, SOAP, and REST APIs ? Monitor and analyze major common network security vulnerabilities ? Develop Software-Defined Networks with Ryu, OpenDaylight, Floodlight, ONOS, and POX Controllers ? Emulate simple and complex networks with Mininet and its extensions for network and systems emulations ? Learn to configure and build network systems and Virtual Network Functions (VNF) in heterogeneous deployment environments ? Explore various Python modules to program the Internet In Detail Python Network Programming Cookbook - Second Edition highlights the major aspects of network programming in Python, starting from writing simple networking clients to developing and deploying complex Software-Defined Networking (SDN) and Network Functions Virtualization (NFV) systems. It creates the building blocks for many practical web and networking applications that rely on various networking protocols. It presents the power and beauty of Python to solve numerous real-world tasks in the area of network programming, network and system administration, network monitoring, and web-application development. In this edition, you will also be introduced to network modelling to build your own cloud network. You will learn about the concepts and fundamentals of SDN and then extend your network with Mininet. Next, you’ll find recipes on Authentication, Authorization, and Accounting (AAA) and open and proprietary SDN approaches and frameworks. You will also learn to configure the Linux Foundation networking ecosystem and deploy and automate your networks with Python in the cloud and the Internet scale. By the end of this book, you will be able to analyze your network security vulnerabilities using advanced network packet capture and analysis techniques. Style and approach This book follows a practical approach and covers major aspects of network programming in Python. It provides hands-on recipes combined with short and concise explanations on code snippets. This book will serve as a supplementary material to develop hands-on skills in any academic course on network programming. This book further elaborates network softwarization, including Software-Defined Networking (SDN), Network Functions Virtualization (NFV), and orchestration. We learn to configure and deploy enterprise network platforms, develop applications on top of them with Python.

Apply Functional Programming techniques to C++ to build highly modular, testable, and reusable code About This Book ? Modularize your applications and make them highly reusable and testable ? Get familiar with complex concepts such as metaprogramming, concurrency, and immutability ? A highly practical guide to building functional code in C++ filled with lots of examples and real-world use cases Who This Book Is For This book is for C++ developers comfortable with OOP who are interested in learning how to apply the functional paradigm to create robust and testable apps. What You Will Learn ? Get to know the difference between imperative and functional approaches ? See the use of first-class functions and pure functions in a functional style ? Discover various techniques to apply immutable state to avoid side effects ? Design a recursive algorithm effectively ? Create faster programs using lazy evaluation ? Structure code using design patterns to make the design process easier ? Use concurrency techniques to develop responsive software ? Learn how to use the C++ Standard Template Library and metaprogramming in a functional way to improve code optimization In Detail Functional programming allows developers to divide programs into smaller, reusable components that ease the creation, testing, and maintenance of software as a whole. Combined with the power of C++, you can develop robust and scalable applications that fulfill modern day software requirements. This book will help you discover all the C++ 17 features that can be applied to build software in a functional way. The book is divided into three modules—the first introduces the fundamentals of functional programming and how it is supported by modern C++. The second module explains how to efficiently implement C++ features such as pure functions and immutable states to build robust applications. The last module describes how to achieve concurrency and apply design patterns to enhance your application’s performance. Here, you will also learn to optimize code using metaprogramming in a functional way. By the end of the book, you will be familiar with the functional approach of programming and will be able to use these techniques on a daily basis. Style and approach This book uses a module-based approach, where each module will cover important aspects of functional programming in C++ and will help you develop efficient and robust applications through gaining a practical understanding.

Extract patterns and knowledge from your data in easy way using MATLAB About This Book ? Get your first steps into machine learning with the help of this easy-to-follow guide ? Learn regression, clustering, classification, predictive analytics, artificial neural networks and more with MATLAB ? Understand how your data works and identify hidden layers in the data with the power of machine learning. Who This Book Is For This book is for data analysts, data scientists, students, or anyone who is looking to get started with machine learning and want to build efficient data processing and predicting applications. A mathematical and statistical background will really help in following this book well. What You Will Learn ? Learn the introductory concepts of machine learning. ? Discover different ways to transform data using SAS XPORT, import and export tools, ? Explore the different types of regression techniques such as simple & multiple linear regression, ordinary least squares estimation, correlations and how to apply them to your data. ? Discover the basics of classification methods and how to implement Naive Bayes algorithm and Decision Trees in the Matlab environment. ? Uncover how to use clustering methods like hierarchical clustering to grouping data using the similarity measures. ? Know how to perform data fitting, pattern recognition, and clustering analysis with the help of MATLAB Neural Network Toolbox. ? Learn feature selection and extraction for dimensionality reduction leading to improved performance. In Detail MATLAB is the language of choice for many researchers and mathematics experts for machine learning. This book will help you build a foundation in machine learning using MATLAB for beginners. You’ll start by getting your system ready with t he MATLAB environment for machine learning and you’ll see how to easily interact with the Matlab workspace. We’ll then move on to data cleansing, mining and analyzing various data types in machine learning and you’ll see how to display data values on a plot. Next, you’ll get to know about the different types of regression techniques and how to apply them to your data using the MATLAB functions. You’ll understand the basic concepts of neural networks and perform data fitting, pattern recognition, and clustering analysis. Finally, you’ll explore feature selection and extraction techniques for dimensionality reduction for performance improvement. At the end of the book, you will learn to put it all together into real-world cases covering major machine learning algorithms and be comfortable in performing machine learning with MATLAB. Style and approach The book takes a very comprehensive approach to enhance your understanding of machine learning using MATLAB. Sufficient real-world examples and use cases are included in the book to help you grasp the concepts quickly and apply them easily in your day-to-day work.

Learn the basics of Geographic Information Systems by solving real-world problems with powerful open source tools About This Book ? This easy-to-follow guide allows you to manage and analyze geographic data with ease using open source tools ? Publish your geographical data online ? Learn the basics of geoinformatics in a practical way by solving problems Who This Book Is For The book is for IT professionals who have little or no knowledge of GIS. It’s also useful for those who are new to the GIS field who don’t want to spend a lot of money buying licenses of commercial tools and training. What You Will Learn ? Collect GIS data for your needs ? Store the data in a PostGIS database ? Exploit the data using the power of the GIS queries ? Analyze the data with basic and more advanced GIS tools ? Publish your data and share it with others ? Build a web map with your published data In Detail The most commonly used GIS tools automate tasks that were historically done manually—compiling new maps by overlaying one on top of the other or physically cutting maps into pieces representing specific study areas, changing their projection, and getting meaningful results from the various layers by applying mathematical functions and operations. This book is an easy-to-follow guide to use the most matured open source GIS tools for these tasks. We’ll start by setting up the environment for the tools we use in the book. Then you will learn how to work with QGIS in order to generate useful spatial data. You will get to know the basics of queries, data management, and geoprocessing. After that, you will start to practice your knowledge on real-world examples. We will solve various types of geospatial analyses with various methods. We will start with basic GIS problems by imitating the work of an enthusiastic real estate agent, and continue with more advanced, but typical tasks by solving a decision problem. Finally, you will find out how to publish your data (and results) on the web. We will publish our data with QGIS Server and GeoServer, and create a basic web map with the API of the lightweight Leaflet web mapping library. Style and approach The book guides you step by step through each of the core concepts of the GIS toolkit, building an overall picture of its capabilities. This guide approaches the topic systematically, allowing you to build upon what you learned in previous chapters. By the end of this book, you’ll have an understanding of the aspects of building a GIS system and will be able to take that knowledge with you to whatever project calls for it.