Get command of your organizational Big Data using the power of data science and analytics About This Book ? A perfect companion to boost your Big Data storing, processing, analyzing skills to help you take informed business decisions ? Work with the best tools such as Apache Hadoop, R, Python, and Spark for NoSQL platforms to perform massive online analyses ? Get expert tips on statistical inference, machine learning, mathematical modeling, and data visualization for Big Data Who This Book Is For The book is intended for existing and aspiring Big Data professionals who wish to become the go-to person in their organization when it comes to Big Data architecture, analytics, and governance. While no prior knowledge of Big Data or related technologies is assumed, it will be helpful to have some programming experience. What You Will Learn ? Get a 360-degree view into the world of Big Data, data science and machine learning ? Broad range of technical and business Big Data analytics topics that caters to the interests of the technical experts as well as corporate IT executives ? Get hands-on experience with industry-standard Big Data and machine learning tools such as Hadoop, Spark, MongoDB, KDB+ and R ? Create production-grade machine learning BI Dashboards using R and R Shiny with step-by-step instructions ? Learn how to combine open-source Big Data, machine learning and BI Tools to create low-cost business analytics applications ? Understand corporate strategies for successful Big Data and data science projects ? Go beyond general-purpose analytics to develop cutting-edge Big Data applications using emerging technologies In Detail Big Data analytics relates to the strategies used by organizations to collect, organize and analyze large amounts of data to uncover valuable business insights that otherwise cannot be analyzed through traditional systems. Crafting an enterprise-scale cost-efficient Big Data and machine learning solution to uncover insights and value from your organization's data is a challenge. Today, with hundreds of new Big Data systems, machine learning packages and BI Tools, selecting the right combination of technologies is an even greater challenge. This book will help you do that. With the help of this guide, you will be able to bridge the gap between the theoretical world of technology with the practical ground reality of building corporate Big Data and data science platforms. You will get hands-on exposure to Hadoop and Spark, build machine learning dashboards using R and R Shiny, create web-based apps using NoSQL databases such as MongoDB and even learn how to write R code for neural networks. By the end of the book, you will have a very clear and concrete understanding of what Big Data analytics means, how it drives revenues for organizations, and how you can develop your own Big Data analytics solution using different tools and methods articulated in this book. Style and approach This book equips you with a knowledge of various NoSQL tools, R, Python programming, cloud platforms, and techniques so you can use them to store, analyze, and deliver meaningful insights from your data.

Learn the techniques for object recognition, 3D reconstruction, stereo imaging, and other computer vision applications using examples on different functions of OpenCV. About This Book ? Learn how to apply complex visual effects to images with OpenCV 3.x and Python ? Extract features from an image and use them to develop advanced applications ? Build algorithms to help you understand image content and perform visual searches ? Get to grips with advanced techniques in OpenCV such as machine learning, artificial neural network, 3D reconstruction, and augmented reality Who This Book Is For This book is intended for Python developers who are new to OpenCV and want to develop computer vision applications with OpenCV and Python. This book is also useful for generic software developers who want to deploy computer vision applications on the cloud. It would be helpful to have some familiarity with basic mathematical concepts such as vectors, matrices, and so on. What You Will Learn ? Detect shapes and edges from images and videos ? How to apply filters on images and videos ? Use different techniques to manipulate and improve images ? Extract and manipulate particular parts of images and videos ? Track objects or colors from videos ? Recognize specific object or faces from images and videos ? How to create Augmented Reality applications ? Apply artificial neural networks and machine learning to improve object recognition In Detail Computer vision is found everywhere in modern technology. OpenCV for Python enables us to run computer vision algorithms in real time. With the advent of powerful machines, we have more processing power to work with. Using this technology, we can seamlessly integrate our computer vision applications into the cloud. Focusing on OpenCV 3.x and Python 3.6, this book will walk you through all the building blocks needed to build amazing computer vision applications with ease. We start off by manipulating images using simple filtering and geometric transformations. We then discuss affine and projective transformations and see how we can use them to apply cool advanced manipulations to your photos like resizing them while keeping the content intact or smoothly removing undesired elements. We will then cover techniques of object tracking, body part recognition, and object recognition using advanced techniques of machine learning such as artificial neural network. 3D reconstruction and augmented reality techniques are also included. The book covers popular OpenCV libraries with the help of examples. This book is a practical tutorial that covers various examples at different levels, teaching you about the different functions of OpenCV and their actual implementation. By the end of this book, you will have acquired the skills to use OpenCV and Python to develop real-world computer vision applications. Style and approach The book is a practical tutorial that covers various examples at different levels, teaching you about the different functions of OpenCV and their actual implementation.

Deploy and manage VMware vSphere 6.5 components with ease. About This Book ? Simplified and to-the-point theory and practical recipes to deploy and manage vSphere 6.5 ? Discover the best ways to deploy stateless and stateful ESXi hosts and upgrade them ? Storage and network resource management ? Certificate management using VMCA ? Monitor the performance of a vSphere environment. Who This Book Is For If you are a system administrator, support professional, or anyone interested in learning how to install, configure, and manage a vSphere environment, then this book is for you. This task-oriented reference guide will also benefit consultants or infrastructure architects who design and deploy vSphere 6.5 environments. What You Will Learn ? Upgrade your existing vSphere environment or perform a fresh deployment. ? Automate the deployment and management of large sets of ESXi hosts in your vSphere Environment ? Configure and manage FC, iSCSI, and NAS storage, and get more control over how storage resources are allocated and managed ? Configure vSphere networking by deploying host-wide and data center-wide switches in your vSphere environment ? Configure high availability on a host cluster and learn how to enable the fair distribution and utilization of compute resources ? Patch and upgrade the vSphere environment ? Handle certificate request generation and renew component certificates ? Monitor performance of a vSphere environment In Detail VMware vSphere is a complete and robust virtualization product suite that helps transform data centers into simplified on-premises cloud infrastructures, providing for the automation and orchestration of workload deployment and life cycle management of the infrastructure. This book focuses on the latest release of VMware vSphere and follows a recipe-based approach, giving you hands-on instructions required to deploy and manage a vSphere environment. The book starts with the procedures involved in upgrading your existing vSphere infrastructure to vSphere 6.5, followed by deploying a new vSphere 6.5 environment. Then the book delves further into the procedures involved in managing storage and network access to the ESXi hosts and the virtual machines running on them. Moving on, the book covers high availability and fair distribution/utilization of clustered compute and storage resources. Finally, the book covers patching and upgrading the vSphere infrastructure using VUM, certificate management using VMCA, and finishes with a chapter covering the tools that can be used to monitor the performance of a vSphere infrastructure. Style and approach This book will quickly get you started with managing VMware components.

Take a deep dive into building data-driven test frameworks using Selenium WebDriver About This Book ? A comprehensive guide to designing data-driven test frameworks using the Selenium 3 WebDriver API, AppiumDriver API, Java-Bindings, and TestNG ? Learn how to use Selenium Page Object Design Patterns and D.R.Y. (Don’t Repeat Yourself) Approaches to software development in automated testing ? Discover the Selenium Grid Architecture and build your own grid for browser and mobile devices ? Use third party tools and services like ExtentReports for results processing, reporting, and SauceLabs for cloud-based test services Who This Book Is For This book is intended for software quality assurance/testing professionals, software project managers, or software developers with prior experience in using Selenium and Java to test web-based applications.This book is geared towards the quality assurance and development professionals responsible for designing and building enterprise-based testing frameworks.The user should have a working knowledge of the Java, TestNG, and Selenium technologies What You Will Learn ? Design the Selenium Driver Class for local, remote, and third party grid support ? Build Page Object Classes using the Selenium Page Object Model ? Develop Data-Driven Test Classes using the TestNG framework ? Encapsulate Data using the JSON Protocol ? Build a Selenium Grid for RemoteWebDriver Testing ? Construct Utility Classes for use in Synchronization, File I/O, Reporting and Test Listener Classes ? Run the sample framework and see the benefits of a live data-driven framework in real-time In Detail The Selenium WebDriver 3.x Technology is an open source API available to test both Browser and Mobile applications. It is completely platform independent in that tests built for one browser or mobile device, will also work on all other browsers and mobile devices. Selenium supports all major development languages which allow it to be tied directly into the technology used to develop the applications. This guide will provide a step-by-step approach to designing and building a data-driven test framework using Selenium WebDriver, Java, and TestNG. The book starts off by introducing users to the Selenium Page Object Design Patterns and D.R.Y Approaches to Software Development. In doing so, it covers designing and building a Selenium WebDriver framework that supports both Browser and Mobile Devices. It will lead the user through a journey of architecting their own framework with a scalable driver class, Java utility classes, JSON Data Provider, Data-Driven Test Classes, and support for third party tools and plugins. Users will learn how to design and build a Selenium Grid from scratch to allow the framework to scale and support different browsers, mobile devices, versions, and platforms, and how they can leverage third party grids in the Cloud like SauceLabs. Other topics covered include designing abstract base and sub-classes, inheritance, dual-driver support, parallel testing, testing multi-branded applications, best practices for using locators, and data encapsulation. Finally, you will be presented with a sample fully-functional framework to get them up and running with the Selenium WebDriver for browser testing. By the end of the book, you will be able to design your own automation testing framework and perform data-driven testing with Selenium WebDriver. Style and approach A comprehensive approach to designing data-driven test frameworks using the Selenium 3 WebDriver API, Java-Bindings, and TestNG Technologies

Discover Android programming and web development by understanding the concepts of Kotlin Programming About This Book ? Practical solutions to your common programming problems with Kotlin 1.1 ? Leverage the functional power of Kotlin to ease your Android application development ? Learn to use Java code in conjunction with Kotlin Who This Book Is For This book will appeal to Kotlin developers keen to find solutions for their common programming problems. Java programming knowledge would be an added advantage. What You Will Learn ? Understand the basics and object-oriented concepts of Kotlin Programming ? Explore the full potential of collection frameworks in Kotlin ? Work with SQLite databases in Android, make network calls, and fetch data over a network ? Use Kotlin's Anko library for efficient and quick Android development ? Uncover some of the best features of Kotlin: Lambdas and Delegates ? Set up web service development environments, write servlets, and build RESTful services with Kotlin ? Learn how to write unit tests, integration tests, and instrumentation/acceptance tests. In Detail The Android team has announced first-class support for Kotlin 1.1. This acts as an added boost to the language and more and more developers are now looking at Kotlin for their application development. This recipe-based book will be your guide to learning the Kotlin programming language. The recipes in this book build from simple language concepts to more complex applications of the language. After the fundamentals of the language, you will learn how to apply the object-oriented programming features of Kotlin 1.1. Programming with Lambdas will show you how to use the functional power of Kotlin. This book has recipes that will get you started with Android programming with Kotlin 1.1, providing quick solutions to common problems encountered during Android app development. You will also be taken through recipes that will teach you microservice and concurrent programming with Kotlin. Going forward, you will learn to test and secure your applications with Kotlin. Finally, this book supplies recipes that will help you migrate your Java code to Kotlin and will help ensure that it's interoperable with Java. Style and approach This book explains concepts related to Kotlin Programming using a practical approach and with the help of easy-to-follow recipes.

The common patterns and practices of the microservice architecture and their application using the Clojure programming language. About This Book ? Relevance of the microservice architecture and benefits of Clojure's functional and simple features to implement it. ? Learn best practices and common principles to avoid common pitfalls while developing microservices. ? Learn how to use Pedestal to build your next microservices, secure them using JWT, and monitor them using the ELK stack Who This Book Is For You should have a working knowledge of programming in Clojure. However, no knowledge of RESTful architecture, microservices, or web services is expected. If you are looking to apply techniques to your own projects, taking your first steps into microservice architecture, this book is for you. What You Will Learn ? Explore the pros and cons of monolithic and microservice architectures ? Use Clojure to effectively build a reallife application using Microservices ? Gain practical knowledge of the Clojure Pedestal framework and how to use it to build Microservices ? Explore various persistence patterns and learn how to use Apache Kafka to build event-driven microservice architectures ? Secure your Microservices using JWT ? Monitor Microservices at scale using the ELK stack ? Deploy Microservices at scale using container orchestration platforms such as Kubernetes In Detail The microservice architecture is sweeping the world as the de facto pattern with which to design and build scalable, easy-tomaintain web applications. This book will teach you common patterns and practices, and will show you how to apply these using the Clojure programming language. This book will teach you the fundamental concepts of architectural design and RESTful communication, and show you patterns that provide manageable code that is supportable in development and at scale in production. We will provide you with examples of how to put these concepts and patterns into practice with Clojure. This book will explain and illustrate, with practical examples, how teams of all sizes can start solving problems with microservices. You will learn the importance of writing code that is asynchronous and non-blocking and how Pedestal helps us do this. Later, the book explains how to build Reactive microservices in Clojure that adhere to the principles underlying the Reactive Manifesto. We finish off by showing you various ways to monitor, test, and secure your microservices. By the end, you will be fully capable of setting up, modifying, and deploying a microservice with Clojure and Pedestal. Style and approach This book highlights the merits of the microservice architecture and its implementation with Clojure. Learn to implement microservices by migrating a monolithic application to a microservice-based architecture.

Learn to use AWS IoT services to build your connected applications with the help of this comprehensive guide. About This Book ? Gets you started with AWS IoT and its functionalities ? Learn different modules of AWS IoT with practical use cases. ? Learn to secure your IoT communication Who This Book Is For This book is for anyone who wants to get started with the AWS IoT Suite and implement it with practical use cases. This book acts as an extensive guide, on completion of which you will be in a position to start building IoT projects using AWS IoT platform and using cloud services for your projects. What You Will Learn ? Implement AWS IoT on IoT projects ? Learn the technical capabilities of AWS IoT and IoT devices ? Create IoT-based AWS IoT projects ? Choose IoT devices and AWS IoT platforms to use based on the kind of project you need to build ? Deploy AWS Greengrass and AWS Lambda ? Develop program for AWS IoT Button ? Visualize IoT AWS data ? Build predictive analytics using AWS IoT and AWS Machine Learning In Detail The Internet of Things market increased a lot in the past few years and IoT development and its adoption have showed an upward trend. Analysis and predictions say that Enterprise IoT platforms are the future of IoT. AWS IoT is currently leading the market with its wide range of device support SDKs and versatile management console. This book initially introduces you to the IoT platforms, and how it makes our IoT development easy. It then covers the complete AWS IoT Suite and how it can be used to develop secure communication between internet-connected things such as sensors, actuators, embedded devices, smart applications, and so on. The book also covers the various modules of AWS: AWS Greengrass, AWS device SDKs, AWS IoT Platform, AWS Button, AWS Management consoles, AWS-related CLI, and API references, all with practical use cases. Near the end, the book supplies security-related best practices to make bi-directional communication more secure. When you've finished this book, you'll be up-and-running with the AWS IoT Suite, and building IoT projects. Style and approach This book is a step-by-step practical guide that helps you learn AWS IoT quickly.

Learn how to write scalable and concurrent programs in Scala, a language that grows with you. About This Book ? Get a grip on the functional features of the Scala programming language ? Understand and develop optimal applications using object-oriented and functional Scala constructs ? Learn reactive principles with Scala and work with the Akka framework Who This Book Is For This book is for programmers who choose to get a grip over Scala to write concurrent, scalable, and reactive programs. No prior experience with any programming language is required to learn the concepts explained in this book. Knowledge of any programming language would help the reader understanding concepts faster though. What You Will Learn ? Get to know the reasons for choosing Scala: its use and the advantages it provides over other languages ? Bring together functional and object-oriented programming constructs to make a manageable application ? Master basic to advanced Scala constructs ? Test your applications using advanced testing methodologies such as TDD ? Select preferred language constructs from the wide variety of constructs provided by Scala ? Make the transition from the object-oriented paradigm to the functional programming paradigm ? Write clean, concise, and powerful code with a functional mindset ? Create concurrent, scalable, and reactive applications utilizing the advantages of Scala In Detail Scala is a general-purpose programming language that supports both functional and object-oriented programming paradigms. Due to its concise design and versatility, Scala's applications have been extended to a wide variety of fields such as data science and cluster computing. You will learn to write highly scalable, concurrent, and testable programs to meet everyday software requirements. We will begin by understanding the language basics, syntax, core data types, literals, variables, and more. From here you will be introduced to data structures with Scala and you will learn to work with higher-order functions. Scala's powerful collections framework will help you get the best out of immutable data structures and utilize them effectively. You will then be introduced to concepts such as pattern matching, case classes, and functional programming features. From here, you will learn to work with Scala's object-oriented features. Going forward, you will learn about asynchronous and reactive programming with Scala, where you will be introduced to the Akka framework. Finally, you will learn the interoperability of Scala and Java. After reading this book, you'll be well versed with this language and its features, and you will be able to write scalable, concurrent, and reactive programs in Scala. Style and approach This book is for programmers who want to master Scala to write concurrent, scalable, and reactive programs. Though no experience with any programming language is needed, some basic knowledge would help understand concepts faster.

Get to grips with the essentials of deep learning by leveraging the power of Python About This Book ? Your one-stop solution to get started with the essentials of deep learning and neural network modeling ? Train different kinds of neural networks to tackle various problems in Natural Language Processing, computer vision, speech recognition, and more ? Covers popular Python libraries such as Tensorflow, Keras, and more, along with tips on training, deploying and optimizing your deep learning models in the best possible manner Who This Book Is For Aspiring data scientists and machine learning experts who have limited or no exposure to deep learning will find this book to be very useful. If you are looking for a resource that gets you up and running with the fundamentals of deep learning and neural networks, this book is for you. As the models in the book are trained using the popular Python-based libraries such as Tensorflow and Keras, it would be useful to have sound programming knowledge of Python. What You Will Learn ? Get to grips with the core concepts of deep learning and neural networks ? Set up deep learning library such as TensorFlow ? Fine-tune your deep learning models for NLP and Computer Vision applications ? Unify different information sources, such as images, text, and speech through deep learning ? Optimize and fine-tune your deep learning models for better performance ? Train a deep reinforcement learning model that plays a game better than humans ? Learn how to make your models get the best out of your GPU or CPU In Detail Deep Learning a trending topic in the field of Artificial Intelligence today and can be considered to be an advanced form of machine learning, which is quite tricky to master. This book will help you take your first steps in training efficient deep learning models and applying them in various practical scenarios. You will model, train, and deploy different kinds of neural networks such as Convolutional Neural Network, Recurrent Neural Network, and will see some of their applications in real-world domains including computer vision, natural language processing, speech recognition, and so on. You will build practical projects such as chatbots, implement reinforcement learning to build smart games, and develop expert systems for image captioning and processing. Popular Python library such as TensorFlow is used in this book to build the models. This book also covers solutions for different problems you might come across while training models, such as noisy datasets, small datasets, and more. This book does not assume any prior knowledge of deep learning. By the end of this book, you will have a firm understanding of the basics of deep learning and neural network modeling, along with their practical applications. Style and approach This step-by-step guide is filled with real-world practical examples and use cases to solve various deep learning problems.

Explore the concepts and tools you need to discover the world of microservices with various design patterns About This Book ? Get to grips with the microservice architecture and build enterprise-ready microservice applications ? Learn design patterns and the best practices while building a microservice application ? Obtain hands-on techniques and tools to create high-performing microservices resilient to possible fails Who This Book Is For This book is for architects and senior developers who would like implement microservice design patterns in their enterprise application development. The book assumes some prior programming knowledge. What You Will Learn ? How to break monolithic application into microservices ? Implement caching strategies, CQRS and event sourcing, and circuit breaker patterns ? Incorporate different microservice design patterns, such as shared data, aggregator, proxy, and chained ? Utilize consolidate testing patterns such as integration, signature, and monkey tests ? Secure microservices with JWT, API gateway, and single sign on ? Deploy microservices with continuous integration or delivery, Blue-Green deployment In Detail Microservices are a hot trend in the development world right now. Many enterprises have adopted this approach to achieve agility and the continuous delivery of applications to gain a competitive advantage. This book will take you through different design patterns at different stages of the microservice application development along with their best practices. Microservice Patterns and Best Practices starts with the learning of microservices key concepts and showing how to make the right choices while designing microservices. You will then move onto internal microservices application patterns, such as caching strategy, asynchronism, CQRS and event sourcing, circuit breaker, and bulkheads. As you progress, you'll learn the design patterns of microservices. The book will guide you on where to use the perfect design pattern at the application development stage and how to break monolithic application into microservices. You will also be taken through the best practices and patterns involved while testing, securing, and deploying your microservice application. At the end of the book, you will easily be able to create interoperable microservices, which are testable and prepared for optimum performance. Style and approach Comprehensive guide that uses architectural patterns with the best choices involved in application development

Build effective regression models in R to extract valuable insights from real data About This Book ? Implement different regression analysis techniques to solve common problems in data science - from data exploration to dealing with missing values ? From Simple Linear Regression to Logistic Regression - this book covers all regression techniques and their implementation in R ? A complete guide to building effective regression models in R and interpreting results from them to make valuable predictions Who This Book Is For This book is intended for budding data scientists and data analysts who want to implement regression analysis techniques using R. If you are interested in statistics, data science, machine learning and wants to get an easy introduction to the topic, then this book is what you need! Basic understanding of statistics and math will help you to get the most out of the book. Some programming experience with R will also be helpful What You Will Learn ? Get started with the journey of data science using Simple linear regression ? Deal with interaction, collinearity and other problems using multiple linear regression ? Understand diagnostics and what to do if the assumptions fail with proper analysis ? Load your dataset, treat missing values, and plot relationships with exploratory data analysis ? Develop a perfect model keeping overfitting, under-fitting, and cross-validation into consideration ? Deal with classification problems by applying Logistic regression ? Explore other regression techniques – Decision trees, Bagging, and Boosting techniques ? Learn by getting it all in action with the help of a real world case study. In Detail Regression analysis is a statistical process which enables prediction of relationships between variables. The predictions are based on the casual effect of one variable upon another. Regression techniques for modeling and analyzing are employed on large set of data in order to reveal hidden relationship among the variables. This book will give you a rundown explaining what regression analysis is, explaining you the process from scratch. The first few chapters give an understanding of what the different types of learning are – supervised and unsupervised, how these learnings differ from each other. We then move to covering the supervised learning in details covering the various aspects of regression analysis. The outline of chapters are arranged in a way that gives a feel of all the steps covered in a data science process – loading the training dataset, handling missing values, EDA on the dataset, transformations and feature engineering, model building, assessing the model fitting and performance, and finally making predictions on unseen datasets. Each chapter starts with explaining the theoretical concepts and once the reader gets comfortable with the theory, we move to the practical examples to support the understanding. The practical examples are illustrated using R code including the different packages in R such as R Stats, Caret and so on. Each chapter is a mix of theory and practical examples. By the end of this book you will know all the concepts and pain-points related to regression analysis, and you will be able to implement your learning in your projects. Style and approach An easy-to-follow step by step guide which will help you get to grips with real world application of Regression Analysis with R

Master the capabilities of PostgreSQL 10 to efficiently manage and maintain your database About This Book ? Your one-stop guide to mastering advanced concepts in PostgreSQL 10 with ease ? Master query optimization, replication, and high availability with PostgreSQL ? Extend the functionalities of your PostgreSQL instance to suit your organizational needs with minimal effort Who This Book Is For If you are a PostgreSQL data architect or an administrator and want to understand how to implement advanced functionalities and master complex administrative tasks with PostgreSQL 10, then this book is perfect for you. Prior experience of administrating a PostgreSQL database and a working knowledge of SQL are required to make the best use of this book. What You Will Learn ? Get to grips with the advanced features of PostgreSQL 10 and handle advanced SQL ? Make use of the indexing features in PostgreSQL and fine-tune the performance of your queries ? Work with stored procedures and manage backup and recovery ? Master replication and failover techniques ? Troubleshoot your PostgreSQL instance for solutions to common and not-so-common problems ? Learn how to migrate your database from MySQL and Oracle to PostgreSQL without any hassle In Detail PostgreSQL is an open source database used for handling large datasets (big data) and as a JSON document database. This book highlights the newly introduced features in PostgreSQL 10, and shows you how you can build better PostgreSQL applications, and administer your PostgreSQL database more efficiently. We begin by explaining advanced database design concepts in PostgreSQL 10, along with indexing and query optimization. You will also see how to work with event triggers and perform concurrent transactions and table partitioning, along with exploring SQL and server tuning. We will walk you through implementing advanced administrative tasks such as server maintenance and monitoring, replication, recovery, high availability, and much more. You will understand common and not-so-common troubleshooting problems and how you can overcome them. By the end of this book, you will have an expert-level command of advanced database functionalities and will be able to implement advanced administrative tasks with PostgreSQL 10. Style and approach This mastering-level guide delves into the advanced functionalities of PostgreSQL 10

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.

Harness the power of Dynamics 365 Operations and discover all you need to implement it About This Book ? Master all the necessary tools and resources to evaluate Dynamics 365 for Operations, implement it, and proactively maintain it. ? Troubleshoot your problems effectively with your Dynamics 365 partner ? Learn about architecture, deployment choices, integration, configuration and data migration, development, testing, reporting and BI, support, upgrading, and more. Who This Book Is For This book is for technology leaders, project managers solution architects, and consultants who are planning to implement, are in the process of implementing, or are currently upgrading to Dynamics 365 for Operations. This book will help you effectively learn and implement Dynamics 365 for Operations. What You Will Learn ? Learn about Microsoft Dynamics 365, it's offerings, plans and details of Finance and Operations, Enterprise edition ? Understand the methodology and the tool, architecture, and deployment options ? Effectively plan and manage configurations and data migration, functional design, and technical design ? Understand integration frameworks, development concepts, best practices, and recommendations while developing new solutions ? Learn how to leverage intelligence and analytics through Power BI, machine learning, IOT, and Cortana intelligence ? Master testing, training, going live, upgrading, and how to get support during and after the implementation In Detail Microsoft Dynamics 365 for Finance and Operations, Enterprise edition, is a modern, cloud-first, mobile-first, ERP solution suitable for medium and large enterprise customers. This book will guide you through the entire life cycle of a implementation, helping you avoid common pitfalls while increasing your efficiency and effectiveness at every stage of the project. Starting with the foundations, the book introduces the Microsoft Dynamics 365 offerings, plans, and products. You will be taken through the various methodologies, architectures, and deployments so you can select, implement, and maintain Microsoft Dynamics 365 for Finance and Operations, Enterprise edition. You will delve in-depth into the various phases of implementation: project management, analysis, configuration, data migration, design, development, using Power BI, machine learning, Cortana analytics for intelligence, testing, training, and finally deployment, support cycles, and upgrading. This book focuses on providing you with information about the product and the various concepts and tools, along with real-life examples from the field and guidance that will empower you to execute and implement Dynamics 365 for Finance and Operations, Enterprise edition. Style and approach This book is a step-by-step guide focusing on implementing Dynamics 365 Operations solutions for your organization.

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 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.

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.

Leverage Scala and Machine Learning to study and construct systems that can learn from data About This Book ? Explore a broad variety of data processing, machine learning, and genetic algorithms through diagrams, mathematical formulation, and updated source code in Scala ? Take your expertise in Scala programming to the next level by creating and customizing AI applications ? Experiment with different techniques and evaluate their benefits and limitations using real-world applications in a tutorial style Who This Book Is For If you’re a data scientist or a data analyst with a fundamental knowledge of Scala who wants to learn and implement various Machine learning techniques, this book is for you. All you need is a good understanding of the Scala programming language, a basic knowledge of statistics, a keen interest in Big Data processing, and this book! What You Will Learn ? Build dynamic workflows for scientific computing ? Leverage open source libraries to extract patterns from time series ? Write your own classification, clustering, or evolutionary algorithm ? Perform relative performance tuning and evaluation of Spark ? Master probabilistic models for sequential data ? Experiment with advanced techniques such as regularization and kernelization ? Dive into neural networks and some deep learning architecture ? Apply some basic multiarm-bandit algorithms ? Solve big data problems with Scala parallel collections, Akka actors, and Apache Spark clusters ? Apply key learning strategies to a technical analysis of financial markets In Detail The discovery of information through data clustering and classification is becoming a key differentiator for competitive organizations. Machine learning applications are everywhere, from self-driving cars, engineering design, logistics, manufacturing, and trading strategies, to detection of genetic anomalies. The book is your one stop guide that introduces you to the functional capabilities of the Scala programming language that are critical to the creation of machine learning algorithms such as dependency injection and implicits. You start by learning data preprocessing and filtering techniques. Following this, you'll move on to unsupervised learning techniques such as clustering and dimension reduction, followed by probabilistic graphical models such as Na?ve Bayes, hidden Markov models and Monte Carlo inference. Further, it covers the discriminative algorithms such as linear, logistic regression with regularization, kernelization, support vector machines, neural networks, and deep learning. You’ll move on to evolutionary computing, multibandit algorithms, and reinforcement learning. Finally, the book includes a comprehensive overview of parallel computing in Scala and Akka followed by a de*ion of Apache Spark and its ML library. With updated codes based on the latest version of Scala and comprehensive examples, this book will ensure that you have more than just a solid fundamental knowledge in machine learning with Scala. Style and approach This book is designed as a tutorial with hands-on exercises using technical analysis of financial markets and corporate data. The approach of each chapter is such that it allows you to understand key concepts easily.

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.

Learn the techniques used by the most successful IT people in the world. About This Book ? Get real-life case studies for different IT roles, developers, testers, analysts, project managers, DBAs ? Identify with your IT scenarios and take the right decision to move up in your career ? Improve your EQ and face any difficult scenario confidently and effectively Who This Book Is For This book is for professionals across the IT domain who work as developers, administrators, architects, administrators system analysts, and so on, who want to create a better working environment around them by improving their own emotional intelligence. This book assumes that you are a beginner to emotional intelligence and will help you understand the basic concepts before helping you with real life scenarios. What You Will Learn ? Improve your observation skills to understand people better ? Know how to identify what motivates you and those around you ? Develop strategies for working more effectively with others ? Increase your capacity to influence people and improve your communication skills ? Understand how to successfully complete tasks through other people ? Discover how to control the emotional content of your decision-making In Detail This book will help you discover your emotional quotient (EQ) through practices and techniques that are used by the most successful IT people in the world. It will make you familiar with the core skills of Emotional Intelligence, such as understanding the role that emotions play in life, especially in the workplace. You will learn to identify the factors that make your behavior consistent, not just to other employees, but to yourself. This includes recognizing, harnessing, predicting, fostering, valuing, soothing, increasing, decreasing, managing, shifting, influencing or turning around emotions and integrating accurate emotional information into decision-making, reasoning, problem solving, etc., because, emotions run business in a way that spreadsheets and logic cannot. When a deadline lurks, you’ll know the steps you need to take to keep calm and composed. You’ll find out how to meet the deadline, and not get bogged down by stress. We’ll explain these factors and techniques through real-life examples faced by IT employees and you’ll learn using the choices that they made. This book will give you a detailed analysis of the events and behavioral pattern of the employees during that time. This will help you improve your own EQ to the extent that you don’t just survive, but thrive in a competitive IT industry. Style and approach You will be taken through real-life events faced by IT employees in different scenarios. These real-world cases are analyzed along with the response of the employees, which will help you to develop your own emotion intelligence quotient and face any difficult scenario confidently and effectively.