If you are a professional, student, or educator who wants to learn to use IPython Notebook as a tool for technical and scientific computing, visualization, and data analysis, this is the book for you. This book will prove valuable for anyone that needs to do computations in an agile environment.

Create solutions that are easy to maintain, quick to upgrade, and follow proven concepts and designs About This Book Design software that is maintainable outside the ecosystem of their creators Ensure quality by following patterns that have been proved to work Over two dozen practical Architectural and Design patterns Who This Book Is For Learning Dynamics NAV Patterns is intended for developers, architects, (technical) consultants, and application managers. You may have very little or no knowledge about NAV patterns, but you should be acquainted with programming. What You Will Learn Apply object-oriented practices to C/AL programming Structure your application to avoid merge conflicts Refactor legacy code and avoid anti-patterns Design decision trees to decide when to use which patterns Clone codes and their application in Dynamics NAV Make your application extensible by creating predefined hooks and facades In Detail Microsoft Dynamics NAV is a complete ERP system, which also contains a robust set of development tools to support customization and enhancement. These include an object designer for each of the seven application object types, a business application oriented programming language with .NET interface capability, a compiler, a debugger, and programming testing language support. Learning Dynamics NAV Patterns will guide you through the NAV way of solving problems. This book will first introduce you to patterns and the software architecture of the NAV and then help you to build an example application. Then, it walks you through the details of architectural patterns, design patterns, and implementation patterns. This book will also talk about anti-patterns and handling legacy code. Finally, it teaches you to build solutions using patterns. Proven patterns and best practices will help you create better solutions that are easy to maintain in larger teams across several locations. It will guide you through combining abstract patterns using easy-to-understand examples and will help you decide which patterns to use in which scenarios. Style and approach This book explains the concepts of patterns, code structuring, and object-oriented concepts in a way that is easy to understand for Dynamics NAV specialists through practical examples.

Unleash Python and take your small readers on an adventurous ride through the world of programming About This Book Learn to start using Python for some simple programming tasks such as doing easy mathematical calculations. Use logic and control loops to build a nice interesting game. Get to grips with working with data and, once you're comfortable with that, you'll be introduced to Pygame, which will help you wrap up the book with a cool game. Who This Book Is For This book is for kids (aged 10 and over). This is book is intended for absolute beginners who lack any knowledge of computing or programming languages and want to get started in the world of programming. What You Will Learn Start fiddling with Python's variables, build functions and interact with users Build your own calculator using the Math Library Train Python to make logical decisions Work with moving 2D objects on-screen Understand the Pygame Library and build your very own game! Write a cool program to manage inventories in your backpack In Detail Kids are always the most fast-paced and enthusiastic learners, and are naturally willing to build stuff that looks like magic at the end (when it works!). Programming can be one such magic. Being able to write a program that works helps them feel they've really achieved something. Kids today are very tech-savvy and cannot wait to enter the fast-paced digital world. Because Python is one of the most popular languages and has a syntax that is quite simple to understand, even kids are eager to use it as a stepping stone to learning programming languages. This book will cover projects that are simple and fun, and teach kids how to write Python code that works. The book will teach the basics of Python programming, installation, and so on and then will move on to projects. A total of three projects, with each and every step explained carefully, without any assumption of previous experience. Style and approach The book will take a light approach in guiding the little readers through the world of Python. The main idea is to teach by example and let the readers have as much exercises to do, so that they learn faster and can apply their own ideas to the existing examples. The book should get them thinking, by the end, on where they can go next with such a powerful tool at their disposal.

Harness the power of multiple computers using Python through this fast-paced informative guide About This Book You'll learn to write data processing programs in Python that are highly available, reliable, and fault tolerant Make use of Amazon Web Services along with Python to establish a powerful remote computation system Train Python to handle data-intensive and resource hungry applications Who This Book Is For This book is for Python developers who have developed Python programs for data processing and now want to learn how to write fast, efficient programs that perform CPU-intensive data processing tasks. What You Will Learn Get an introduction to parallel and distributed computing See synchronous and asynchronous programming Explore parallelism in Python Distributed application with Celery Python in the Cloud Python on an HPC cluster Test and debug distributed applications In Detail CPU-intensive data processing tasks have become crucial considering the complexity of the various big data applications that are used today. Reducing the CPU utilization per process is very important to improve the overall speed of applications. This book will teach you how to perform parallel execution of computations by distributing them across multiple processors in a single machine, thus improving the overall performance of a big data processing task. We will cover synchronous and asynchronous models, shared memory and file systems, communication between various processes, synchronization, and more. Style and Approach This example based, step-by-step guide will show you how to make the best of your hardware configuration using Python for distributing applications.

Explore the power of React components for cutting-edge web development About This Book Learn to build better websites by creating a variety of different components in React Conceptualize the design and build maintainable web apps with the help of components A fast-paced guide to help you learn about component-based development in React Who This Book Is For This book is ideal for developers who are familiar with the basics of React and are looking for a guide to building a wide range of components as well as develop component-driven UIs. What You Will Learn How to structure an app into components Working with nested components Work with nested components Set up communication across components Style the existing components Work with Material Design as a component Render components on the server Make the best of design patterns Make the app pluggable In Detail The reader will learn how to use React and its component-based architecture in order to develop modern user interfaces. A new holistic way of thinking about UI development will establish throughout this book and the reader will discover the power of React components with many examples. After reading the book and following the example application, the reader has built a small to a mid-size application with React using a component based UI architecture. The book will take the reader through a journey to discover the benefits of component-based user interfaces over the classical MVC architecture. Throughout the book, the reader will develop a wide range of components and then bring them together to build a component-based UI. By the end of this book, readers would have learned several techniques to build powerful components and how the component-based development is beneficial over regular web development. Style and approach This book is a compact, example-driven guide that provides a step-by-step approach.

Familiarize yourself with probabilistic graphical models through real-world problems and illustrative code examples in R About This Book Predict and use a probabilistic graphical models (PGM) as an expert system Comprehend how your computer can learn Bayesian modeling to solve real-world problems Know how to prepare data and feed the models by using the appropriate algorithms from the appropriate R package Who This Book Is For This book is for anyone who has to deal with lots of data and draw conclusions from it, especially when the data is noisy or uncertain. Data scientists, machine learning enthusiasts, engineers, and those who curious about the latest advances in machine learning will find PGM interesting. What You Will Learn Understand the concepts of PGM and which type of PGM to use for which problem Tune the model’s parameters and explore new models automatically Understand the basic principles of Bayesian models, from simple to advanced Transform the old linear regression model into a powerful probabilistic model Use standard industry models but with the power of PGM Understand the advanced models used throughout today's industry See how to compute posterior distribution with exact and approximate inference algorithms In Detail Probabilistic graphical models (PGM, also known as graphical models) are a marriage between probability theory and graph theory. Generally, PGMs use a graph-based representation. Two branches of graphical representations of distributions are commonly used, namely Bayesian networks and Markov networks. R has many packages to implement graphical models. We’ll start by showing you how to transform a classical statistical model into a modern PGM and then look at how to do exact inference in graphical models. Proceeding, we’ll introduce you to many modern R packages that will help you to perform inference on the models. We will then run a Bayesian linear regression and you’ll see the advantage of going probabilistic when you want to do prediction. Next, you’ll master using R packages and implementing its techniques. Finally, you’ll be presented with machine learning applications that have a direct impact in many fields. Here, we’ll cover clustering and the discovery of hidden information in big data, as well as two important methods, PCA and ICA, to reduce the size of big problems. Style and approach This book gives you a detailed and step-by-step explanation of each mathematical concept, which will help you build and analyze your own machine learning models and apply them to real-world problems. The mathematics is kept simple and each formula is explained thoroughly.

A hands-on guide enriched with examples to master deep reinforcement learning algorithms with Python About This Book ? Your entry point into the world of artificial intelligence using the power of Python ? An example-rich guide to master various RL and DRL algorithms ? Explore various state-of-the-art architectures along with math Who This Book Is For If you’re a machine learning developer or deep learning enthusiast interested in artificial intelligence and want to learn about reinforcement learning from scratch, this book is for you. Some knowledge of linear algebra, calculus, and the Python programming language will help you understand the concepts covered in this book. What You Will Learn ? Understand the basics of reinforcement learning methods, algorithms, and elements ? Train an agent to walk using OpenAI Gym and Tensorflow ? Understand the Markov Decision Process, Bellman’s optimality, and TD learning ? Solve multi-armed-bandit problems using various algorithms ? Master deep learning algorithms, such as RNN, LSTM, and CNN with applications ? Build intelligent agents using the DRQN algorithm to play the Doom game ? Teach agents to play the Lunar Lander game using DDPG ? Train an agent to win a car racing game using dueling DQN In Detail Reinforcement Learning (RL) is the trending and most promising branch of artificial intelligence. Hands-On Reinforcement learning with Python will help you master not only the basic reinforcement learning algorithms but also the advanced deep reinforcement learning algorithms. The book starts with an introduction to Reinforcement Learning followed by OpenAI Gym, and TensorFlow. You will then explore various RL algorithms and concepts, such as Markov Decision Process, Monte Carlo methods, and dynamic programming, including value and policy iteration. This example-rich guide will introduce you to deep reinforcement learning algorithms, such as Dueling DQN, DRQN, A3C, PPO, and TRPO. You will also learn about imagination-augmented agents, learning from human preference, DQfD, HER, and many more of the recent advancements in reinforcement learning. By the end of the book, you will have all the knowledge and experience needed to implement reinforcement learning and deep reinforcement learning in your projects, and you will be all set to enter the world of artificial intelligence. Style and approach This is a hands-on book designed to further expand your machine learning skills by understanding reinforcement to deep reinforcement learning algorithms with applications in Python.

Enhance the power of NumPy and start boosting your scientific computing capabilities About This Book ? Grasp all aspects of numerical computing and understand NumPy ? Explore examples to learn exploratory data analysis (EDA), regression, and clustering ? Access NumPy libraries and use performance benchmarking to select the right tool Who This Book Is For Mastering Numerical Computing with NumPy is for you if you are a Python programmer, data analyst, data engineer, or a data science enthusiast, who wants to master the intricacies of NumPy and build solutions for your numeric and scientific computational problems. You are expected to have familiarity with mathematics to get the most out of this book. What You Will Learn ? Perform vector and matrix operations using NumPy ? Perform exploratory data analysis (EDA) on US housing data ? Develop a predictive model using simple and multiple linear regression ? Understand unsupervised learning and clustering algorithms with practical use cases ? Write better NumPy code and implement the algorithms from scratch ? Perform benchmark tests to choose the best configuration for your system In Detail NumPy is one of the most important scientific computing libraries available for Python. Mastering Numerical Computing with NumPy teaches you how to achieve expert level competency to perform complex operations, with in-depth coverage of advanced concepts. Beginning with NumPy's arrays and functions, you will familiarize yourself with linear algebra concepts to perform vector and matrix math operations. You will thoroughly understand and practice data processing, exploratory data analysis (EDA), and predictive modeling. You will then move on to working on practical examples which will teach you how to use NumPy statistics in order to explore US housing data and develop a predictive model using simple and multiple linear regression techniques. Once you have got to grips with the basics, you will explore unsupervised learning and clustering algorithms, followed by understanding how to write better NumPy code while keeping advanced considerations in mind. The book also demonstrates the use of different high-performance numerical computing libraries and their relationship with NumPy. You will study how to benchmark the performance of different configurations and choose the best for your system. By the end of this book, you will have become an expert in handling and performing complex data manipulations. Style and approach This mastering guide will help you master your skills required to perform a complex numerical computation. The book contains the right mixture of theory and practical examples that will help you in dealing with the advanced NumPy and build solutions for your numeric and scientific computational problems

Test your C++ programming skills by solving real-world programming problems covered in the book About This Book ? Solve a variety of real-world programming and logic problems by leveraging the power of C++17 ? Test your skills in using language features, algorithms, data structures, design patterns, and more ? Explore areas such as cryptography, communication, and image handling in C++ Who This Book Is For This book will appeal to C++ developers of all levels. There's a challenge inside for everyone. What You Will Learn ? Serialize and deserialize JSON and XML data ? Perform encryption and signing to facilitate secure communication between parties ? Embed and use SQLite databases in your applications ? Use threads and asynchronous functions to implement generic purpose parallel algorithms ? Compress and decompress files to/from a ZIP archive ? Implement data structures such as circular buffer and priority queue ? Implement general purpose algorithms as well as algorithms that solve specific problems ? Create client-server applications that communicate over TCP/IP ? Consume HTTP REST services ? Use design patterns to solve real-world problems In Detail C++ is one of the most widely-used programming languages and has applications in a variety of fields, such as gaming, GUI programming, and operating systems, to name a few. Through the years, C++ has evolved into (and remains) one of the top choices for software developers worldwide. This book will show you some notable C++ features and how to implement them to meet your application needs. Each problem is unique and doesn't just test your knowledge of the language; it tests your ability to think out of the box and come up with the best solutions. With varying levels of difficulty, you'll be faced with a wide variety of challenges. And in case you're stumped, you don't have to worry: we've got the best solutions to the problems in the book. So are you up for the challenge? Style and approach A recipe-based approach where each problem is solved with the help of step by step instructions.

Photoshop: A Step by Step Ultimate Beginners’ Guide to Mastering Adobe Photoshop in 1 Week

Master the art of testing and automating your SOA using SoapUI About This Book Design real-time test automation frameworks for Enterprise applications using SoapUI Learn how to solve test automation issues for complex systems A complete guide to understanding SOA automation from quality assurance to business assurance Who This Book Is For The book is intended for test architects, SOA test specialists, automation testers, test managers, and software developers who have a good understanding of SOA, web services, Groovy Scripting, and the SOAP UI tool. What You Will Learn Familiarize yourself with Test Web services from functional, nonfunctional, and security aspects Learn to test real-time service orchestrations Design test automation solutions for SOA-based Enterprise applications Learn multilayer test automation Selenium plus SoapUI under a single umbrella Integrate your SoapUI framework with Jenkins In Detail SoapUI is an open-source cross-platform testing application that provides complete test coverage and supports all the standard protocols and technologies. This book includes real-time examples of implementing SoapUI to achieve quality and business assurance. Starting with the features and functionalities of SoapUI, the book will then focus on functional testing, load testing, and security testing of web services. Furthermore, you will learn how to automate your services and then design data-driven, keyword-driven, and hybrid-driven frameworks in SoapUI. Then the book will show you how to test UIs and services using SoapUI with the help of Selenium. You will also learn how to integrate SoapUI with Jenkins for CI and SoapUI test with QC with backward- and forward-compatibility. The final part of the book will show you how to virtualize a service response in SoapUI using Service Mocking. You will finish the journey by discovering the best practices for SoapUI test automation and preparing yourself for the online certification of SoapUI. Style and approach Filled with real-time examples, this book will help readers take their knowledge to the next level. This book is a comprehensive guide that will cover the end-to-end life cycle of implementing SoapUI in various phases of software testing and the software development life cycle.

Taking a highly practical approach and a playful tone, Kali Linux CTF Blueprints provides step-by-step guides to setting up vulnerabilities, in-depth guidance to exploiting them, and a variety of advice and ideas to build and customize your own challenges. If you are a penetration testing team leader or individual who wishes to challenge yourself or your friends in the creation of penetration testing assault courses, this is the book for you. The book assumes a basic level of penetration skills and familiarity with the Kali Linux operating system.

This book is intended for developers who have some familiarity with Apache Karaf and who want a quick reference for practical, proven tips on how to perform common tasks such as configuring Pax modules deployed in Apache Karaf, Extending HttpService with Apache Karaf. You should have working knowledge of Apache karaf, as the book provides a deeper understanding of the capabilities of Apache Karaf.

This is a step-by-step, tutorial guide designed to help readers transition from beginners to more experienced developers using clear explanations. The variety of examples will help readers build, secure, and host real-time web applications. If you are a developer who wants to use PHP and MariaDB to build web applications, this book is ideal for you. Beginners can use this book to start with the basics and learn how to build and host web applications. Seasoned PHP Developers can use this book to get familiar with the new features of PHP 5.4 and 5.5, unit testing, caching, security, and performance optimization.

If you are a system administrator who is interested in implementing and managing open source virtualization infrastructures, this is the book for you. A basic knowledge of virtualization and basic Linux command line experience is needed.

Make web applications run faster by using advanced PHP, SQL and JavaScript techniques About This Book ? Use a customized PHP stack to create efficient data-driven web applications ? Ensure seamless implementation of a JavaScript & HTML 5 CSS based frontend and PHP based backend. ? Learn about problem identification, best strategies, and UI design patterns as well to build a clean, fast web application Who This Book Is For The audience for this book would be PHP developers who have some basic knowledge of PHP programming and Web technologies. JavaScript programming knowledge is not necessary. What You Will Learn ? Install, confgure, and use profling and benchmarking testing tools ? Understand how to recognize optimizable data structures and functions to effectively optimize a PHP7 application ? Diagnose bad SQL query performance and discover ways to optimize it ? Grasp modern SQL techniques to optimize complex SQL queries ? Identify and simplify overly complex JavaScript code ? Explore and implement UI design principles that effectively enhance the performance ? Combine web technologies to boost web server performance In Detail This book will get you started with the latest benchmarking, profiling and monitoring tools for PHP, MySQL and JavaScript using Docker-based technologies. From optimizing PHP 7 code to learning asynchronous programming, from implementing Modern SQL solutions to discovering Functional JavaScript techniques, this book covers all the latest developments in Faster Web technologies. You will not only learn to determine the best optimization strategies, but also how to implement them. Along the way, you will learn how to profile your PHP scripts with Blackfire.io, monitor your Web applications, measure database performance, optimize SQL queries, explore Functional JavaScript, boost Web server performance in general and optimize applications when there is nothing left to optimize by going beyond performance. After reading this book, you will know how to boost the performance of any Web application and make it part of what has come to be known as the Faster Web. Style and approach The book has a step by step practical approach to developing highly efficient Web applications, with many practical and useful code snippets.

A starter guide that covers Apache Flume in detail.Apache Flume: Distributed Log Collection for Hadoop is intended for people who are responsible for moving datasets into Hadoop in a timely and reliable manner like software engineers, database administrators, and data warehouse administrators

This practical guide will teach you how deep learning (DL) can be used to solve complex real-world problems. About This Book ? Explore deep reinforcement learning (RL), from the first principles to the latest algorithms ? Evaluate high-profile RL methods, including value iteration, deep Q-networks, policy gradients, TRPO, PPO, DDPG, D4PG, evolution strategies and genetic algorithms ? Keep up with the very latest industry developments, including AI-driven chatbots Who This Book Is For Some fluency in Python is assumed. Basic deep learning (DL) approaches should be familiar to readers and some practical experience in DL will be helpful. This book is an introduction to deep reinforcement learning (RL) and requires no background in RL. What You Will Learn ? Understand the DL context of RL and implement complex DL models ? Learn the foundation of RL: Markov decision processes ? Evaluate RL methods including Cross-entropy, DQN, Actor-Critic, TRPO, PPO, DDPG, D4PG and others ? Discover how to deal with discrete and continuous action spaces in various environments ? Defeat Atari arcade games using the value iteration method ? Create your own OpenAI Gym environment to train a stock trading agent ? Teach your agent to play Connect4 using AlphaGo Zero ? Explore the very latest deep RL research on topics including AI-driven chatbots In Detail Recent developments in reinforcement learning (RL), combined with deep learning (DL), have seen unprecedented progress made towards training agents to solve complex problems in a human-like way. Google's use of algorithms to play and defeat the well-known Atari arcade games has propelled the field to prominence, and researchers are generating new ideas at a rapid pace. Deep Reinforcement Learning Hands-On is a comprehensive guide to the very latest DL tools and their limitations. You will evaluate methods including Cross-entropy and policy gradients, before applying them to real-world environments. Take on both the Atari set of virtual games and family favorites such as Connect4. The book provides an introduction to the basics of RL, giving you the know-how to code intelligent learning agents to take on a formidable array of practical tasks. Discover how to implement Q-learning on 'grid world' environments, teach your agent to buy and trade stocks, and find out how natural language models are driving the boom in chatbots. Style and approach Deep Reinforcement Learning Hands-On explains the art of building self-learning agents using algorithms and practical examples. Experiment with famous examples, such as Google's defeat of well-known Atari arcade games.

Become a master at penetration testing using machine learning with Python About This Book ? Identify ambiguities and breach intelligent security systems ? Perform unique cyber attacks to breach robust systems ? Learn to leverage machine learning algorithms Who This Book Is For This book is for pen testers and security professionals who are interested in learning techniques to break an intelligent security system. Basic knowledge of Python is needed, but no prior knowledge of machine learning is necessary. What You Will Learn ? Take an in-depth look at machine learning ? Get to know natural language processing (NLP) ? Understand malware feature engineering ? Build generative adversarial networks using Python libraries ? Work on threat hunting with machine learning and the ELK stack ? Explore the best practices for machine learning In Detail Cyber security is crucial for both businesses and individuals. As systems are getting smarter, we now see machine learning interrupting computer security. With the adoption of machine learning in upcoming security products, it’s important for pentesters and security researchers to understand how these systems work, and to breach them for testing purposes. This book begins with the basics of machine learning and the algorithms used to build robust systems. Once you’ve gained a fair understanding of how security products leverage machine learning, you'll dive into the core concepts of breaching such systems. Through practical use cases, you’ll see how to find loopholes and surpass a self-learning security system. As you make your way through the chapters, you’ll focus on topics such as network intrusion detection and AV and IDS evasion. We’ll also cover the best practices when identifying ambiguities, and extensive techniques to breach an intelligent system. By the end of this book, you will be well-versed with identifying loopholes in a self-learning security system and will be able to efficiently breach a machine learning system. Style and approach This book takes a step-by-step approach to identify the loop holes in a self-learning security system. You will be able to efficiently breach a machine learning system with the help of best practices towards the end of the book.

Foster your NLP applications with the help of deep learning, NLTK, and TensorFlow Key Features * Weave neural networks into linguistic applications across various platforms * Perform NLP tasks and train its models using NLTK and TensorFlow * Boost your NLP models with strong deep learning architectures such as CNNs and RNNs Book Description Natural language processing (NLP) has found its application in various domains, such as web search, advertisements, and customer services, and with the help of deep learning, we can enhance its performances in these areas. Hands-On Natural Language Processing with Python teaches you how to leverage deep learning models for performing various NLP tasks, along with best practices in dealing with today’s NLP challenges. To begin with, you will understand the core concepts of NLP and deep learning, such as Convolutional Neural Networks (CNNs), recurrent neural networks (RNNs), semantic embedding, Word2vec, and more. You will learn how to perform each and every task of NLP using neural networks, in which you will train and deploy neural networks in your NLP applications. You will get accustomed to using RNNs and CNNs in various application areas, such as text classification and sequence labeling, which are essential in the application of sentiment analysis, customer service chatbots, and anomaly detection. You will be equipped with practical knowledge in order to implement deep learning in your linguistic applications using Python's popular deep learning library, TensorFlow. By the end of this book, you will be well versed in building deep learning-backed NLP applications, along with overcoming NLP challenges with best practices developed by domain experts. What you will learn *Implement semantic embedding of words to classify and find entities *Convert words to vectors by training in order to perform arithmetic operations *Train a deep learning model to detect classification of tweets and news *Implement a question-answer model with search and RNN models *Train models for various text classification datasets using CNN *Implement WaveNet a deep generative model for producing a natural-sounding voice *Convert voice-to-text and text-to-voice *Train a model to convert speech-to-text using DeepSpeech Who this book is for Hands-on Natural Language Processing with Python is for you if you are a developer, machine learning or an NLP engineer who wants to build a deep learning application that leverages NLP techniques. This comprehensive guide is also useful for deep learning users who want to extend their deep learning skills in building NLP applications. All you need is the basics of machine learning and Python to enjoy the book.

Develop modern user interfaces using Angular 6 and its component-based architecture. Key Features * Build better web applications with highly scalable concepts using Angular * Learn new ways to design your web applications * Build a fully functional web application that lets you tackle real-world user interface problems using Angular components Book Description Angular framework embraces a mature user interface (UI) component architecture, a powerful tool when developing scalable application interfaces. The simple and deterministic design of Angular components supports you in building large and scalable component-based applications. Mastering Angular Components covers a new holistic way of thinking about UI development, and helps you discover the power of Angular 6 components through various examples. The book starts with an introduction to component-based user interfaces and how Angular 6 manages this concept. Following a step-by-step approach, you will build a fully functional task-management application using Angular. You’ll start with basic layout components, adding some core task-management components before completing the first draft of your application. You will then move on to working through a refactoring exercise in order to learn how to enhance the way you deal with states and data. Once you have got to grips with all this, you will study how to make use of the Angular router within your application. By the end of this book, you will be able to constantly refine the functionality of your application and create components that render SVG graphics, add a time-tracking feature, visualize data using third-party library Chartist, and even create a plugin architecture using Angular components. What you will learn * Use TypeScript to create Angular 6 components * Leverage component composition to solve complex UI requirements * Build an architecture using pure components and container components * Explore the basics of RxJS observable streams and use them to build your application reactively * Communicate between components using child queries * Implement the Angular router to make your application navigable * Build reusable and dynamic graphical content using Angular components and SVG * Integrate third-party libraries such as Moment.js and Chartist into your existing Angular application Who this book is for Mastering Angular Components is for you if you are an Angular developer who already has a good understanding of basic frontend web technologies such as JavaScript, HTML, and CSS.