Explore the world of neural networks by building powerful deep learning models using the R ecosystem Key Features * Get to grips with the fundamentals of deep learning and neural networks * Use R 3.5 and its libraries and APIs to build deep learning models for computer vision and text processing * Implement effective deep learning systems in R with the help of end-to-end projects Book Description Deep learning finds practical applications in several domains, while R is the preferred language for designing and deploying deep learning models. This Learning Path introduces you to the basics of deep learning and even teaches you to build a neural network model from scratch. As you make your way through the chapters, you’ll explore deep learning libraries and understand how to create deep learning models for a variety of challenges, right from anomaly detection to recommendation systems. The book will then help you cover advanced topics, such as generative adversarial networks (GANs), transfer learning, and large-scale deep learning in the cloud, in addition to model optimization, overfitting, and data augmentation. Through real-world projects, you’ll also get up to speed with training convolutional neural networks (CNNs), recurrent neural networks (RNNs), and long short-term memory networks (LSTMs) in R. By the end of this Learning Path, you’ll be well versed with deep learning and have the skills you need to implement a number of deep learning concepts in your research work or projects. This Learning Path includes content from the following Packt products: * R Deep Learning Essentials - Second Edition by F. Wiley and Mark Hodnett * R Deep Learning Projects by Yuxi (Hayden) Liu and Pablo Maldonado What you will learn * Implement credit card fraud detection with autoencoders * Train neural networks to perform handwritten digit recognition using MXNet * Reconstruct images using variational autoencoders * Explore the applications of autoencoder neural networks in clustering and dimensionality reduction * Create natural language processing (NLP) models using Keras and TensorFlow in R * Prevent models from overfitting the data to improve generalizability * Build shallow neural network prediction models Who this book is for This Learning Path is for aspiring data scientists, data analysts, machine learning developers, and deep learning enthusiasts who are well versed in machine learning concepts and are looking to explore the deep learning paradigm using R. A fundamental understanding of R programming and familiarity with the basic concepts of deep learning are necessary to get the most out of this Learning Path.

Master machine learning techniques with real-world projects that interface TensorFlow with R, H2O, MXNet, and other languages Key Features * Gain expertise in machine learning, deep learning and other techniques * Build intelligent end-to-end projects for finance, social media, and a variety of domains * Implement multi-class classification, regression, and clustering Book Description R is one of the most popular languages when it comes to exploring the mathematical side of machine learning and easily performing computational statistics. This Learning Path shows you how to leverage the R ecosystem to build efficient machine learning applications that carry out intelligent tasks within your organization. You'll tackle realistic projects such as building powerful machine learning models with ensembles to predict employee attrition. You'll explore different clustering techniques to segment customers using wholesale data and use TensorFlow and Keras-R for performing advanced computations. You’ll also be introduced to reinforcement learning along with its various use cases and models. Additionally, it shows you how some of these black-box models can be diagnosed and understood. By the end of this Learning Path, you’ll be equipped with the skills you need to deploy machine learning techniques in your own projects. This Learning Path includes content from the following Packt products: * R Machine Learning Projects by Dr. Sunil Kumar Chinnamgari * Mastering Machine Learning with R - Third Edition by Cory Lesmeister What you will learn * Develop a joke recommendation engine to recommend jokes that match users’ tastes * Build autoencoders for credit card fraud detection * Work with image recognition and convolutional neural networks * Make predictions for casino slot machine using reinforcement learning * Implement NLP techniques for sentiment analysis and customer segmentation * Produce simple and effective data visualizations for improved insights * Use NLP to extract insights for text * Implement tree-based classifiers including random forest and boosted tree Who this book is for If you are a data analyst, data scientist, or machine learning developer this is an ideal Learning Path for you. Each project will help you test your skills in implementing machine learning algorithms and techniques. A basic understanding of machine learning and working knowledge of R programming is necessary to get the most out of this Learning Path.

Apply modern reinforcement learning and deep reinforcement learning methods using Python and its powerful libraries Key Features * 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 the power of modern Python libraries to gain confidence in building self-trained applications Book Description Reinforcement Learning (RL) is the trending and most promising branch of artificial intelligence. This Learning Path will help you master not only the basic reinforcement learning algorithms but also the advanced deep reinforcement learning algorithms. The Learning Path starts with an introduction to RL followed by OpenAI Gym, and TensorFlow. You will then explore various RL algorithms, such as Markov Decision Process, Monte Carlo methods, and dynamic programming, including value and policy iteration. You'll also work on various datasets including image, text, and video. This example-rich guide will introduce you to deep RL algorithms, such as Dueling DQN, DRQN, A3C, PPO, and TRPO. You will gain experience in several domains, including gaming, image processing, and physical simulations. You'll explore TensorFlow and OpenAI Gym to implement algorithms that also predict stock prices, generate natural language, and even build other neural networks. You will also learn about imagination-augmented agents, learning from human preference, DQfD, HER, and many of the recent advancements in RL. By the end of the Learning Path, you will have all the knowledge and experience needed to implement RL and deep RL in your projects, and you enter the world of artificial intelligence to solve various real-life problems. This Learning Path includes content from the following Packt products: * Hands-On Reinforcement Learning with Python by Sudharsan Ravichandiran * Python Reinforcement Learning Projects by Sean Saito, Yang Wenzhuo, and Rajalingappaa Shanmugamani What you will learn * Train an agent to walk using OpenAI Gym and TensorFlow * Solve multi-armed-bandit problems using various algorithms * Build intelligent agents using the DRQN algorithm to play the Doom game * Teach your agent to play Connect4 using AlphaGo Zero * Defeat Atari arcade games using the value iteration method * Discover how to deal with discrete and continuous action spaces in various environments Who this book is for If you’re an ML/DL enthusiast interested in AI and want to explore RL and deep RL from scratch, this Learning Path is for you. Prior knowledge of linear algebra is expected.

Build Machine Learning models with a sound statistical understanding. About This Book ? Learn about the statistics behind powerful predictive models with p-value, ANOVA, and F- statistics. ? Implement statistical computations programmatically for supervised and unsupervised learning through K-means clustering. ? Master the statistical aspect of Machine Learning with the help of this example-rich guide to R and Python. Who This Book Is For This book is intended for developers with little to no background in statistics, who want to implement Machine Learning in their systems. Some programming knowledge in R or Python will be useful. What You Will Learn ? Understand the Statistical and Machine Learning fundamentals necessary to build models ? Understand the major differences and parallels between the statistical way and the Machine Learning way to solve problems ? Learn how to prepare data and feed models by using the appropriate Machine Learning algorithms from the more-than-adequate R and Python packages ? Analyze the results and tune the model appropriately to your own predictive goals ? Understand the concepts of required statistics for Machine Learning ? Introduce yourself to necessary fundamentals required for building supervised & unsupervised deep learning models ? Learn reinforcement learning and its application in the field of artificial intelligence domain In Detail Complex statistics in Machine Learning worry a lot of developers. Knowing statistics helps you build strong Machine Learning models that are optimized for a given problem statement. This book will teach you all it takes to perform complex statistical computations required for Machine Learning. You will gain information on statistics behind supervised learning, unsupervised learning, reinforcement learning, and more. Understand the real-world examples that discuss the statistical side of Machine Learning and familiarize yourself with it. You will also design programs for performing tasks such as model, parameter fitting, regression, classification, density collection, and more. By the end of the book, you will have mastered the required statistics for Machine Learning and will be able to apply your new skills to any sort of industry problem. Style and approach This practical, step-by-step guide will give you an understanding of the Statistical and Machine Learning fundamentals you'll need to build models.

Advanced analytics on your Big Data with latest Apache Spark 2.x About This Book ? An advanced guide with a combination of instructions and practical examples to extend the most up-to date Spark functionalities. ? Extend your data processing capabilities to process huge chunk of data in minimum time using advanced concepts in Spark. ? Master the art of real-time processing with the help of Apache Spark 2.x Who This Book Is For If you are a developer with some experience with Spark and want to strengthen your knowledge of how to get around in the world of Spark, then this book is ideal for you. Basic knowledge of Linux, Hadoop and Spark is assumed. Reasonable knowledge of Scala is expected. What You Will Learn ? Examine Advanced Machine Learning and DeepLearning with MLlib, SparkML, SystemML, H2O and DeepLearning4J ? Study highly optimised unified batch and real-time data processing using SparkSQL and Structured Streaming ? Evaluate large-scale Graph Processing and Analysis using GraphX and GraphFrames ? Apply Apache Spark in Elastic deployments using Jupyter and Zeppelin Notebooks, Docker, Kubernetes and the IBM Cloud ? Understand internal details of cost based optimizers used in Catalyst, SystemML and GraphFrames ? Learn how specific parameter settings affect overall performance of an Apache Spark cluster ? Leverage Scala, R and python for your data science projects In Detail Apache Spark is an in-memory cluster-based parallel processing system that provides a wide range of functionalities such as graph processing, machine learning, stream processing, and SQL. This book aims to take your knowledge of Spark to the next level by teaching you how to expand Spark’s functionality and implement your data flows and machine/deep learning programs on top of the platform. The book commences with an overview of the Spark ecosystem. It will introduce you to Project Tungsten and Catalyst, two of the major advancements of Apache Spark 2.x. You will understand how memory management and binary processing, cache-aware computation, and code generation are used to speed things up dramatically. The book extends to show how to incorporate H20, SystemML, and Deeplearning4j for machine learning, and Jupyter Notebooks and Kubernetes/Docker for cloud-based Spark. During the course of the book, you will learn about the latest enhancements to Apache Spark 2.x, such as interactive querying of live data and unifying DataFrames and Datasets. You will also learn about the updates on the APIs and how DataFrames and Datasets affect SQL, machine learning, graph processing, and streaming. You will learn to use Spark as a big data operating system, understand how to implement advanced analytics on the new APIs, and explore how easy it is to use Spark in day-to-day tasks. Style and approach This book is an extensive guide to Apache Spark modules and tools and shows how Spark's functionality can be extended for real-time processing and storage with worked examples.

Run blazingly fast queries on complex graph datasets with the power of the Neo4j graph database About This Book ? Get acquainted with graph database systems and apply them in real-world use cases ? Use Cypher query language, APOC and other Neo4j extensions to derive meaningful analysis from complex data sets. ? A practical guide filled with ready to use examples on querying, graph processing and visualizing information to build smarter spatial applications. Who This Book Is For This book is for developers who want an alternative way to store and process data within their applications. No previous graph database experience is required; however, some basic database knowledge will help you understand the concepts more easily. What You Will Learn ? Understand the science of graph theory, databases and its advantages over traditional databases. ? Install Neo4j, model data and learn the most common practices of traversing data ? Learn the Cypher query language and tailor-made procedures to analyze and derive meaningful representations of data ? Improve graph techniques with the help of precise procedures in the APOC library ? Use Neo4j advanced extensions and plugins for performance optimization. ? Understand how Neo4j's new security features and clustering architecture are used for large scale deployments. In Detail Neo4j is a graph database that allows traversing huge amounts of data with ease. This book aims at quickly getting you started with the popular graph database Neo4j. Starting with a brief introduction to graph theory, this book will show you the advantages of using graph databases along with data modeling techniques for graph databases. You'll gain practical hands-on experience with commonly used and lesser known features for updating graph store with Neo4j's Cypher query language. Furthermore, you'll also learn to create awesome procedures using APOC and extend Neo4j's functionality, enabling integration, algorithmic analysis, and other advanced spatial operation capabilities on data. Through the course of the book you will come across implementation examples on the latest updates in Neo4j, such as in-graph indexes, scaling, performance improvements, visualization, data refactoring techniques, security enhancements, and much more. By the end of the book, you'll have gained the skills to design and implement modern spatial applications, from graphing data to unraveling business capabilities with the help of real-world use cases. Style and approach A step-by-step approach of adopting Neo4j, the world's leading graph database. This book includes a lot of background information, helps you grasp the fundamental concepts behind this radical new way of dealing with connected data, and will give you lots of examples of use cases and environments where a graph database would be a great fit

Get a problem-solution approach enriched with code examples for practical and easy comprehension About This Book ? Explore the use of more than 40 best-of-breed plug-ins for improving efficiency ? Secure and maintain Jenkins 2.x by integrating it with LDAP and CAS, which is a Single Sign-on solution ? Efficiently build advanced pipelines with pipeline as code, thus increasing your team's productivity Who This Book Is For If you are a Java developer, a software architect, a technical project manager, a build manager, or a development or QA engineer, then this book is ideal for you. A basic understanding of the software development life cycle and Java development is needed, as well as a rudimentary understanding of Jenkins. What You Will Learn ? Install and Configure Jenkins 2.x on AWS and Azure ? Explore effective ways to manage and monitor Jenkins 2.x ? Secure Jenkins 2.x using Matrix-based Security ? Deploying a WAR file from Jenkins 2.x to Azure App Services and AWS Beanstalk ? Automate deployment of application on AWS and Azure PaaS ? Continuous Testing – Unit Test Execution, Functional Testing and Load Testing In Detail Jenkins 2.x is one of the most popular Continuous Integration servers in the market today. It was designed to maintain, secure, communicate, test, build, and improve the software development process. This book will begin by guiding you through steps for installing and configuring Jenkins 2.x on AWS and Azure. This is followed by steps that enable you to manage and monitor Jenkins 2.x. You will also explore the ways to enhance the overall security of Jenkins 2.x. You will then explore the steps involved in improving the code quality using SonarQube. Then, you will learn the ways to improve quality, followed by how to run performance and functional tests against a web application and web services. Finally, you will see what the available plugins are, concluding with best practices to improve quality. Style and approach This book provides a problem-solution approach to some common tasks and some uncommon tasks using Jenkins 2.x and is well-illustrated with practical code examples.

Master the ArcGIS API for JavaScript to build web and mobile applications using this practical guide. About This Book ? Develop ArcGIS Server applications with JavaScript, both for traditional web browsers as well as the mobile platform ? Make your maps informative with intuitive geographic layers, user interface widgets, and more ? Integrate ArcGIS content into your custom applications and perform analytics with the ArcGIS Online Who This Book Is For If you are a web or mobile application developer, who wants to create GIS applications in your respective platform, this book is ideal for you. You will need Java Script programming experience to get the most out of this book. Although designed as an introductory to intermediate level book, it will also be useful for more advanced developers who are new to the topic of developing applications with ArcGIS Server. What You Will Learn ? To create an application with the ArcGIS API for JavaScript ? Build and display a broad range of different geometry types to represent features on the map ? The best way to leverage a feature layer and display related attribute data ? The functionality of the wide range of widgets and how to use them effectively ? Query data to gain new insights into the information it contains ? Work with tasks to discover and locate features on the map ? Using the geocoder and associated widgets ? The ability of the API to provide turn by turn directions and routing capabilities ? How to use the Geometry Engine and Geometry Service tasks for common geoprocessing operations ? Integrate content on ArcGIS online and add it to your custom web mapping application In Detail The ArcGIS API for JavaScript enables you to quickly build web and mobile mapping applications that include sophisticated GIS capabilities, yet are easy and intuitive for the user. Aimed at both new and experienced web developers, this practical guide gives you everything you need to get started with the API. After a brief introduction to HTML/CSS/JavaScript, you'll embed maps in a web page, add the tiled, dynamic, and streaming data layers that your users will interact with, and mark up the map with graphics. You will learn how to quickly incorporate a broad range of useful user interface elements and GIS functionality to your application with minimal effort using prebuilt widgets. As the book progresses, you will discover and use the task framework to query layers with spatial and attribute criteria, search for and identify features on the map, geocode addresses, perform network analysis and routing, and add custom geoprocessing operations. Along the way, we cover exciting new features such as the client-side geometry engine, learn how to integrate content from ArcGIS.com, and use your new skills to build mobile web mapping applications. We conclude with a look at version 4 of the ArcGIS API for JavaScript (which is being developed in parallel with version 3.x) and what it means for you as a developer. Style and approach Readers will be taken through a series of exercises that will demonstrate how to efficiently build ArcGIS Server applications for the mobile and web.

Take tiny steps to enter the big world of data science through this interesting guide About This Book ? Learn the fundamentals of machine learning and build your own intelligent applications ? Master the art of building your own machine learning systems with this example-based practical guide ? Work with important classification and regression algorithms and other machine learning techniques Who This Book Is For This book is for anyone interested in entering the data science stream with machine learning. Basic familiarity with Python is assumed. What You Will Learn ? Exploit the power of Python to handle data extraction, manipulation, and exploration techniques ? Use Python to visualize data spread across multiple dimensions and extract useful features ? Dive deep into the world of analytics to predict situations correctly ? Implement machine learning classification and regression algorithms from scratch in Python ? Be amazed to see the algorithms in action ? Evaluate the performance of a machine learning model and optimize it ? Solve interesting real-world problems using machine learning and Python as the journey unfolds In Detail Data science and machine learning are some of the top buzzwords in the technical world today. A resurging interest in machine learning is due to the same factors that have made data mining and Bayesian analysis more popular than ever. This book is your entry point to machine learning. This book starts with an introduction to machine learning and the Python language and shows you how to complete the setup. Moving ahead, you will learn all the important concepts such as, exploratory data analysis, data preprocessing, feature extraction, data visualization and clustering, classification, regression and model performance evaluation. With the help of various projects included, you will find it intriguing to acquire the mechanics of several important machine learning algorithms – they are no more obscure as they thought. Also, you will be guided step by step to build your own models from scratch. Toward the end, you will gather a broad picture of the machine learning ecosystem and best practices of applying machine learning techniques. Through this book, you will learn to tackle data-driven problems and implement your solutions with the powerful yet simple language, Python. Interesting and easy-to-follow examples, to name some, news topic classification, spam email detection, online ad click-through prediction, stock prices forecast, will keep you glued till you reach your goal. Style and approach This book is an enticing journey that starts from the very basics and gradually picks up pace as the story unfolds. Each concept is first succinctly defined in the larger context of things, followed by a detailed explanation of their application. Every concept is explained with the help of a project that solves a real-world problem, and involves hands-on work—giving you a deep insight into the world of machine learning. With simple yet rich language—Python—you will understand and be able to implement the examples with ease.

Mastering Drupal can lead to a mighty website - discover what Drupal 8 can really do with hidden techniques, best practices, and more! About This Book ? The most up-to-date advanced practical guide on Drupal 8 with an in-depth look at all the advanced new features such as authoring, HTML markup, built-in web services, and more ? If you are looking to dive deep into Drupal 8 and create industry-standard web apps, then this is the ideal book for you ? All the code and examples are explained in great detail to help you in the development process Who This Book Is For This book is ideally suited to web developers, designers, and web administrators who want to dive deep into Drupal. Previous experience with Drupal is a must to unleash the full potential of this book. What You Will Learn ? Discover how to better manage content using custom blocks and views ? Display content in multiple ways, taking advantage of display modes ? Create custom modules with YAML and Symfony 2 ? Easily translate content using the new multilingual capabilities ? Use RESTful services and JavaScript frameworks to build headless websites ? Manage Drupal configuration from one server to another easily In Detail Drupal is an open source content management system trusted by governments and organizations around the globe to run their websites. It brings with it extensive content authoring tools, reliable performance, and a proven track record of security. The community of more than 1,000,000 developers, designers, editors, and others have developed and maintained a wealth of modules, themes, and other add-ons to help you build a dynamic web experience. Drupal 8 is the latest release of the Drupal built on the Symfony2 framework. This is the largest change to the Drupal project in its history. The entire API of Drupal has been rebuilt using Symfony and everything from the administrative UI to themes to custom module development has been affected. This book will cover everything you need to plan and build a complete website using Drupal 8. It will provide a clear and concise walkthrough of the more than 200 new features and improvements introduced in Drupal core. In this book, you will learn advanced site building techniques, create and modify themes using Twig, create custom modules using the new Drupal API, explore the new REST and Multilingual functionality, import, and export Configuration, and learn how to migrate from earlier versions of Drupal. Style and approach This book takes a practical approach with equal emphasis on examples and illustrative screenshots.

A guide to mastering Visual Studio 2017 About This Book ? Focus on coding with the new, improved, and powerful tools of VS 2017 ? Master improved debugging and unit testing support capabilities ? Accelerate cloud development with the built-in Azure tools Who This Book Is For .NET Developers who would like to master the new features of VS 2017, and would like to delve into newer areas such as cloud computing, would benefit from this book. Basic knowledge of previous versions of Visual Studio is assumed. What You Will Learn ? Learn what's new in the Visual Studio 2017 IDE, C# 7.0, and how it will help developers to improve their productivity ? Learn the workloads and components of the new installation wizard and how to use the online and offline installer ? Build stunning Windows apps using Windows Presentation Foundation (WPF) and Universal Windows Platform (UWP) tools ? Get familiar with .NET Core and learn how to build apps targeting this new framework ? Explore everything about NuGet packages ? Debug and test your applications using Visual Studio 2017 ? Accelerate cloud development with Microsoft Azure ? Integrate Visual Studio with most popular source control repositories, such as TFS and GitHub In Detail Visual Studio 2017 is the all-new IDE released by Microsoft for developers, targeting Microsoft and other platforms to build stunning Windows and web apps. Learning how to effectively use this technology can enhance your productivity while simplifying your most common tasks, allowing you more time to focus on your project. With this book, you will learn not only what VS2017 offers, but also what it takes to put it to work for your projects. Visual Studio 2017 is packed with improvements that increase productivity, and this book will get you started with the new features introduced in Visual Studio 2017 IDE and C# 7.0. Next, you will learn to use XAML tools to build classic WPF apps, and UWP tools to build apps targeting Windows 10. Later, you will learn about .NET Core and then explore NuGet, the package manager for the Microsoft development platform. Then, you will familiarize yourself with the debugging and live unit testing techniques that comes with the IDE. Finally, you'll adapt Microsoft's implementation of cloud computing with Azure, and the Visual Studio integration with Source Control repositories. Style and approach This comprehensive guide covers the advanced features of Visual Studio 2017, and communicates them through a practical approach to explore the underlying concepts of how, when, and why to use it.

Leverage the power of Python to collect, process, and mine deep insights from social media data About This Book ? Acquire data from various social media platforms such as Facebook, Twitter, YouTube, GitHub, and more ? Analyze and extract actionable insights from your social data using various Python tools ? A highly practical guide to conducting efficient social media analytics at scale Who This Book Is For If you are a programmer or a data analyst familiar with the Python programming language and want to perform analyses of your social data to acquire valuable business insights, this book is for you. The book does not assume any prior knowledge of any data analysis tool or process. What You Will Learn ? Understand the basics of social media mining ? Use PyMongo to clean, store, and access data in MongoDB ? Understand user reactions and emotion detection on Facebook ? Perform Twitter sentiment analysis and entity recognition using Python ? Analyze video and campaign performance on YouTube ? Mine popular trends on GitHub and predict the next big technology ? Extract conversational topics on public internet forums ? Analyze user interests on Pinterest ? Perform large-scale social media analytics on the cloud In Detail Social Media platforms such as Facebook, Twitter, Forums, Pinterest, and YouTube have become part of everyday life in a big way. However, these complex and noisy data streams pose a potent challenge to everyone when it comes to harnessing them properly and benefiting from them. This book will introduce you to the concept of social media analytics, and how you can leverage its capabilities to empower your business. Right from acquiring data from various social networking sources such as Twitter, Facebook, YouTube, Pinterest, and social forums, you will see how to clean data and make it ready for analytical operations using various Python APIs. This book explains how to structure the clean data obtained and store in MongoDB using PyMongo. You will also perform web scraping and visualize data using Scrappy and Beautifulsoup. Finally, you will be introduced to different techniques to perform analytics at scale for your social data on the cloud, using Python and Spark. By the end of this book, you will be able to utilize the power of Python to gain valuable insights from social media data and use them to enhance your business processes. Style and approach This book follows a step-by-step approach to teach readers the concepts of social media analytics using the Python programming language. To explain various data analysis processes, real-world datasets are used wherever required.

Learn everything you need to build highly scalable, robust web applications using Angular release 4 About This Book ? Apply best practices and design patterns to achieve higher scalability in your Angular applications ? Understand the latest features of Angular and create your own components ? Get acquainted with powerful, advanced techniques in Angular to build professional web applications Who This Book Is For This book is for JavaScript developers with some prior exposure to Angular, at least through basic examples. We assume that you’ve got working knowledge of HTML, CSS, and JavaScript. What You Will Learn ? Implement asynchronous programming using Angular ? Beautify your application with the UI components built to the material design specification ? Secure your web application from unauthorized users ? Create complex forms, taking full advantage of 2-way data binding ? Test your Angular applications using the Jasmine and Protractor frameworks for better efficiency ? Learn how to integrate Angular with Bootstrap to create compelling web applications ? Use Angular built-in classes to apply animation in your app In Detail Got some experience of Angular under your belt? Want to learn everything about using advanced features for developing websites? This book is everything you need for the deep understanding of Angular that will set you apart from the developer crowd. Angular has introduced a new way to build applications. Creating complex and rich web applications, with a lighter resource footprint, has never been easier or faster. Angular is now at release 4, with significant changes through previous versions. This book has been written and tested for Angular release 4. Angular is a mature technology, and you'll likely have applications built with earlier versions. This book starts by showing you best practices and approaches to migrating your existing Angular applications so that you can be immediately up-to-date. You will take an in-depth look at components and see how to control the user journey in your applications by implementing routing and navigation. You will learn how to work with asynchronous programming by using Observables. To easily build applications that look great, you will learn all about template syntax and how to beautify applications with Material Design. Mastering forms and data binding will further speed up your application development time. Learning about managing services and animations will help you to progressively enhance your applications. Next you’ll use native directives to integrate Bootstrap with Angular. You will see the best ways to test your application with the leading options such as Jasmine and Protractor. At the end of the book, you’ll learn how to apply design patterns in Angular, and see the benefits they will bring to your development. Style and approach This book provides comprehensive coverage of all aspects of development with Angular. You will learn about all the most powerful Angular concepts, with examples and best practices. This book is everything you need for the deep understanding of Angular that will set you apart from the developer crowd.

Create reports and solve common report problems with minimal fuss. About This Book ? Use this unique book to master the basics and advanced features of Pentaho 8 Reporting. ? A book showing developers and analysts with IT skills how to create and use the best possible reports using the Pentaho platform. ? Written with a very practical approach: full of tutorials and practical examples (source code included). Who This Book Is For This book is written for two types of professionals and students: Information Technologists with a basic knowledge of Databases and Java Developers with medium seniority. Developers will be interested to discover how to embed reports in a third-party Java application. What You Will Learn ? The basics of Pentaho Reporting (Designer and SDK) and its initial setup. ? Develop the most attractive reports on top of a wide range of data sources. ? Perform detailed customization of layout, parameterization, internationalization, behaviors, and more for your custom reports developed with Pentaho Reporting. ? Integrate Pentaho reports into third-party Java application with full control over interactions, layout, and behavior in general. ? Use Pentaho reports in the other components of the Pentaho Suite (BA Platform and PDI). In Detail This hands-on tutorial, filled with exercises and examples, introduces the reader to a variety of concepts within Pentaho Reporting. With screenshots that show you how reports look at design time as well as how they should look when rendered as PDF, Excel, HTML, Text, Rich-Text-File, XML, and CSV, this book also contains complete example source code that you can copy and paste into your environment to get up-and-running quickly. Updated to cover the features of Pentaho 8, this book will teach you everything you need to know to build fast, efficient reports using Pentaho. If your interest lies in the technical details of creating reports and you want to see how to solve common reporting problems with a minimum of fuss, this is the book for you. Style and approach A step-by-step guide covering technical topics relating to environments, best practices, and source code, to enable the reader to assemble the best reports and use them in existing Java applications.

Plan, design, and deploy System Center Configuration Manager 1706 like never before, regardless of how complex your infrastructure is About This Book ? The most up-to-date resource on deploying or migrating to System Center Configuration Manager 1706 within your IT infrastructure ? Plan, design, and deploy ConfigMgr 1706 with ease, both on primary and multiple-hierarchy sites ? Master the new features of ConfigMgr 1706, including Windows 10 support Who This Book Is For If you are a system engineer or an administrator planning to deploy Microsoft System Center Configuration Manager 1706, then this book is for you. This book will also benefit system administrators who are responsible for designing and deploying one or more System CenterConfiguration Manager 1706 sites in their new or existing systems. What You Will Learn ? Install ConfigMgr servers and the necessary roles ? Design and scale ConfigMgr environments ? Configure and administrate essential ConfigMgr roles and features ? Create software packages using .msi and .exe files ? Deliver detailed reports with an automatic patching process ? Apply proper hardening on your deployment and secure workstations ? Deploy operating systems and updates leveraging ConfigMgr mechanisms ? Create high-availability components using the built-in mechanism for backup and recovery In Detail It becomes important to plan, design, and deploy configurations when administrators know that Configuration Manager interacts with a number of infrastructure components such as Active Directory Domain Services, network protocols, Windows Server services, and so on. Via real-world-world deployment scenarios, this book will help you implement a single primary site or multiples sites. You will be able to efficiently plan and deploy a multiple-site hierarchy such as central administration site. Next, you will learn various methods to plan and deploy Configuration Manager clients, secure them and make the most of new features offered through ConfigMgr 1706 like compliance, deploying updates operating systems to the endpoints. Then, this book will show you how to install, configure, and run SQL reports to extract information. Lastly, you will also learn how to create and manage users access in an ConfigMgr environment By the end of this book, you will have learned to use the built-in mechanism to back up and restore data and also design maintenance plan. Style and approach This step-by-step guide teaches you cool ways to plan, deploy, and configure ConfigMgr 1706. This tutorial, which complements the release of ConfigMgr 1706 with a refreshing new approach and expert guidance, will teach you everything you need to know about the essentials of server.

Over 80 recipes to help you breeze through your data analysis projects using R About This Book ? Analyse your data using the popular R packages like ggplot2 with ready-to-use and customizable recipes ? Find meaningful insights from your data and generate dynamic reports ? A practical guide to help you put your data analysis skills in R to practical use Who This Book Is For This book is for data scientists, analysts and even enthusiasts who want to learn and implement the various data analysis techniques using R in a practical way. Those looking for quick, handy solutions to common tasks and challenges in data analysis will find this book to be very useful. Basic knowledge of statistics and R programming is assumed. What You Will Learn ? Acquire, format and visualize your data using R ? Using R to perform an Exploratory data analysis ? Introduction to machine learning algorithms such as classification and regression ? Get started with social network analysis ? Generate dynamic reporting with Shiny ? Get started with geospatial analysis ? Handling large data with R using Spark and MongoDB ? Build Recommendation system- Collaborative Filtering, Content based and Hybrid ? Learn real world dataset examples- Fraud Detection and Image Recognition In Detail Data analytics with R has emerged as a very important focus for organizations of all kinds. R enables even those with only an intuitive grasp of the underlying concepts, without a deep mathematical background, to unleash powerful and detailed examinations of their data. This book will show you how you can put your data analysis skills in R to practical use, with recipes catering to the basic as well as advanced data analysis tasks. Right from acquiring your data and preparing it for analysis to the more complex data analysis techniques, the book will show you how you can implement each technique in the best possible manner. You will also visualize your data using the popular R packages like ggplot2 and gain hidden insights from it. Starting with implementing the basic data analysis concepts like handling your data to creating basic plots, you will master the more advanced data analysis techniques like performing cluster analysis, and generating effective analysis reports and visualizations. Throughout the book, you will get to know the common problems and obstacles you might encounter while implementing each of the data analysis techniques in R, with ways to overcoming them in the easiest possible way. By the end of this book, you will have all the knowledge you need to become an expert in data analysis with R, and put your skills to test in real-world scenarios. Style and Approach ? Hands-on recipes to walk through data science challenges using R ? Your one-stop solution for common and not-so-common pain points while performing real-world problems to execute a series of tasks. ? Addressing your common and not-so-common pain points, this is a book that you must have on the shelf

Simplify machine learning model implementations with Spark About This Book ? Solve the day-to-day problems of data science with Spark ? This unique cookbook consists of exciting and intuitive numerical recipes ? Optimize your work by acquiring, cleaning, analyzing, predicting, and visualizing your data Who This Book Is For This book is for Scala developers with a fairly good exposure to and understanding of machine learning techniques, but lack practical implementations with Spark. A solid knowledge of machine learning algorithms is assumed, as well as hands-on experience of implementing ML algorithms with Scala. However, you do not need to be acquainted with the Spark ML libraries and ecosystem. What You Will Learn ? Get to know how Scala and Spark go hand-in-hand for developers when developing ML systems with Spark ? Build a recommendation engine that scales with Spark ? Find out how to build unsupervised clustering systems to classify data in Spark ? Build machine learning systems with the Decision Tree and Ensemble models in Spark ? Deal with the curse of high-dimensionality in big data using Spark ? Implement Text analytics for Search Engines in Spark ? Streaming Machine Learning System implementation using Spark In Detail Machine learning aims to extract knowledge from data, relying on fundamental concepts in computer science, statistics, probability, and optimization. Learning about algorithms enables a wide range of applications, from everyday tasks such as product recommendations and spam filtering to cutting edge applications such as self-driving cars and personalized medicine. You will gain hands-on experience of applying these principles using Apache Spark, a resilient cluster computing system well suited for large-scale machine learning tasks. This book begins with a quick overview of setting up the necessary IDEs to facilitate the execution of code examples that will be covered in various chapters. It also highlights some key issues developers face while working with machine learning algorithms on the Spark platform. We progress by uncovering the various Spark APIs and the implementation of ML algorithms with developing classification systems, recommendation engines, text analytics, clustering, and learning systems. Toward the final chapters, we’ll focus on building high-end applications and explain various unsupervised methodologies and challenges to tackle when implementing with big data ML systems. Style and approach This book is packed with intuitive recipes supported with line-by-line explanations to help you understand how to optimize your work flow and resolve problems when working with complex data modeling tasks and predictive algorithms. This is a valuable resource for data scientists and those working on large scale data projects.

Build simple, maintainable, and easy to deploy machine learning applications. About This Book ? Build simple, but powerful, machine learning applications that leverage Go’s standard library along with popular Go packages. ? Learn the statistics, algorithms, and techniques needed to successfully implement machine learning in Go ? Understand when and how to integrate certain types of machine learning model in Go applications. Who This Book Is For This book is for Go developers who are familiar with the Go syntax and can develop, build, and run basic Go programs. If you want to explore the field of machine learning and you love Go, then this book is for you! Machine Learning with Go will give readers the practical skills to perform the most common machine learning tasks with Go. Familiarity with some statistics and math topics is necessary. What You Will Learn ? Learn about data gathering, organization, parsing, and cleaning. ? Explore matrices, linear algebra, statistics, and probability. ? See how to evaluate and validate models. ? Look at regression, classification, clustering. ? Learn about neural networks and deep learning ? Utilize times series models and anomaly detection. ? Get to grip with techniques for deploying and distributing analyses and models. ? Optimize machine learning workflow techniques In Detail The mission of this book is to turn readers into productive, innovative data analysts who leverage Go to build robust and valuable applications. To this end, the book clearly introduces the technical aspects of building predictive models in Go, but it also helps the reader understand how machine learning workflows are being applied in real-world scenarios. Machine Learning with Go shows readers how to be productive in machine learning while also producing applications that maintain a high level of integrity. It also gives readers patterns to overcome challenges that are often encountered when trying to integrate machine learning in an engineering organization. The readers will begin by gaining a solid understanding of how to gather, organize, and parse real-work data from a variety of sources. Readers will then develop a solid statistical toolkit that will allow them to quickly understand gain intuition about the content of a dataset. Finally, the readers will gain hands-on experience implementing essential machine learning techniques (regression, classification, clustering, and so on) with the relevant Go packages. Finally, the reader will have a solid machine learning mindset and a powerful Go toolkit of techniques, packages, and example implementations. Style and approach This book connects the fundamental, theoretical concepts behind Machine Learning to practical implementations using the Go programming language.

Over 100 hands-on recipes to build web applications easily and efficiently IN Spring 5.0 About This Book ? Solve real-world problems using the latest features of the Spring framework like Reactive Streams and the Functional Web Framework. ? Learn how to use dependency injection and aspect-oriented programming to write compartmentalized and testable code. ? Understand when to choose between Spring MVC and Spring Web Reactive for your projects Who This Book Is For Java developers who would like to gain in-depth knowledge of how to overcome problems that they face while developing great Spring applications. It will also cater to Spring enthusiasts, users and experts who need an arena for comparative analysis, new ideas and inquiries on some details regarding Spring 5.0 and its previous releases. A basic knowledge of Spring development is essential What You Will Learn ? Understand how functional programming and concurrency in JDK 1.9 works, and how it will affect Spring 5.0 ? Learn the importance and application of reactive programming in creating services, and also the process of creating asynchronous MVC applications ? Implement different Spring Data modules ? Integrate Spring Security to the container ? Create applications and deploy using Spring Boot ? Conceptualize the architecture behind Microservices and learn the details of its implementation ? Create different test cases for the components of Spring 5.0 components In Detail The Spring framework has been the go-to framework for Java developers for quite some time. It enhances modularity, provides more readable code, and enables the developer to focus on developing the application while the underlying framework takes care of transaction APIs, remote APIs, JMX APIs, and JMS APIs. The upcoming version of the Spring Framework has a lot to offer, above and beyond the platform upgrade to Java 9, and this book will show you all you need to know to overcome common to advanced problems you might face. Each recipe will showcase some old and new issues and solutions, right from configuring Spring 5.0 container to testing its components. Most importantly, the book will highlight concurrent processes, asynchronous MVC and reactive programming using Reactor Core APIs. Aside from the core components, this book will also include integration of third-party technologies that are mostly needed in building enterprise applications. By the end of the book, the reader will not only be well versed with the essential concepts of Spring, but will also have mastered its latest features in a solution-oriented manner. Style and Approach This book follows a cookbook style approach, presenting a problem and showing you how to overcome it with useful recipes. The examples provided will help you code along as you learn.

An effective guide to becoming an AWS Certified Developer About This Book ? This fast-paced guide will help you clear the exam with confidence ? Learn to design, develop, and deploy cloud-based solutions using AWS ? Enhance your AWS skills with practice questions and mock tests Who This Book Is For This book is for IT professionals and developers looking to clear the AWS Certified Developer – Associate 2017 exam. Developers looking to develop and manage their applications on the AWS platform will also find this book useful. No prior AWS experience is needed. What You Will Learn ? Create and manage users, groups, and permissions using AWS Identity and Access Management services ? Create a secured Virtual Private Cloud (VPC) with Public and Private Subnets, Network Access Control, and Security groups ? Get started with Elastic Compute Cloud (EC2), launching your first EC2 instance, and working with it ? Handle application traffic with Elastic Load Balancing (ELB) and monitor AWS resources with CloudWatch ? Work with AWS storage services such as Simple Storage Service (S3), Glacier, and CloudFront ? Get acquainted with AWS DynamoDB – a NoSQL database service ? Coordinate work across distributed application components using Simple Workflow Service (SWF) In Detail AWS Certified Developer - Associate Guide starts with a quick introduction to AWS and the prerequisites to get you started. Then, this book gives you a fair understanding of core AWS services and basic architecture. Next, this book will describe about getting familiar with Identity and Access Management (IAM) along with Virtual private cloud (VPC). Moving ahead you will learn about Elastic Compute cloud (EC2) and handling application traffic with Elastic Load Balancing (ELB). Going ahead you we will talk about Monitoring with CloudWatch, Simple storage service (S3) and Glacier and CloudFront along with other AWS storage options. Next we will take you through AWS DynamoDB – A NoSQL Database Service, Amazon Simple Queue Service (SQS) and CloudFormation Overview. Finally, this book covers understanding Elastic Beanstalk and overview of AWS lambda. At the end of this book, we will cover enough topics, tips and tricks along with mock tests for you to be able to pass the AWS Certified Developer - Associate exam and develop as well as manage your applications on the AWS platform. Style and approach This step-by-step guide includes exercises and mock tests to clear the AWS certification exam and become a successful AWS developer.

Master the art of making Docker more extensible, composable, and modular by leveraging plugins and other supporting tools About This Book Get the first book on the market that shows you how to extend the capabilities of Docker using plugins and third-party tools Master the skills of creating various plugins and integrating great tools in order to enhance the functionalities of Docker A practical and learning guide that ensures your investment in Docker becomes more valuable Who This Book Is For This book is for developers and sys admins who are well versed Docker and have knowledge on basic programming languages. If you can’t wait to extend Docker and customize it to meet your requirements, this is the book for you! What You Will Learn Find out about Docker plugins and the problems they solve Gain insights into creating your own plugin Use Docker tools to extend the basic functionality of the core Docker engine Get to grips with the installation and configuration of third-party tools available to use with Docker plugins Install, configure, and use a scheduling service to manage the containers in your environment Enhance your day-to-day Docker usage through security, troubleshooting, and best practices In Detail With Docker, it is possible to get a lot of apps running on the same old servers, making it very easy to package and ship programs. The ability to extend Docker using plugins and load third-party plugins is incredible, and organizations can massively benefit from it. In this book, you will read about what first and third party tools are available to extend the functionality of your existing Docker installation and how to approach your next Docker infrastructure deployment. We will show you how to work with Docker plugins, install it, and cover its lifecycle. We also cover network and volume plugins, and you will find out how to build your own plugin. You’ll discover how to integrate it with Puppet, Ansible, Jenkins, Flocker, Rancher, Packer, and more with third-party plugins. Then, you’ll see how to use Schedulers such as Kubernetes and Amazon ECS. Finally, we’ll delve into security, troubleshooting, and best practices when extending Docker. By the end of this book, you will learn how to extend Docker and customize it based on your business requirements with the help of various tools and plugins. Style and approach An easy to follow guide with plenty of hands-on practical examples which can be executed both on your local machine or externally hosted services.