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

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.

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.

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.

Store, search, and analyze your data with ease using Elasticsearch 5.x About This Book ? Get to grips with the basics of Elasticsearch concepts and its APIs, and use them to create efficient applications ? Create large-scale Elasticsearch clusters and perform analytics using aggregation ? This comprehensive guide will get you up and running with Elasticsearch 5.x in no time Who This Book Is For If you want to build efficient search and analytics applications using Elasticsearch, this book is for you. It will also benefit developers who have worked with Lucene or Solr before and now want to work with Elasticsearch. No previous knowledge of Elasticsearch is expected. What You Will Learn ? See how to set up and configure Elasticsearch and Kibana ? Know how to ingest structured and unstructured data using Elasticsearch ? Understand how a search engine works and the concepts of relevance and scoring ? Find out how to query Elasticsearch with a high degree of performance and scalability ? Improve the user experience by using autocomplete, geolocation queries, and much more ? See how to slice and dice your data using Elasticsearch aggregations. ? Grasp how to use Kibana to explore and visualize your data ? Know how to host on Elastic Cloud and how to use the latest X-Pack features such as Graph and Alerting In Detail Elasticsearch is a modern, fast, distributed, scalable, fault tolerant, and open source search and analytics engine. You can use Elasticsearch for small or large applications with billions of documents. It is built to scale horizontally and can handle both structured and unstructured data. Packed with easy-to- follow examples, this book will ensure you will have a firm understanding of the basics of Elasticsearch and know how to utilize its capabilities efficiently. You will install and set up Elasticsearch and Kibana, and handle documents using the Distributed Document Store. You will see how to query, search, and index your data, and perform aggregation-based analytics with ease. You will see how to use Kibana to explore and visualize your data. Further on, you will learn to handle document relationships, work with geospatial data, and much more, with this easy-to-follow guide. Finally, you will see how you can set up and scale your Elasticsearch clusters in production environments. Style and approach This comprehensive guide will get you started with Elasticsearch 5.x, so you build a solid understanding of the basics. Every topic is explained in depth and is supplemented with practical examples to enhance your understanding.

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.

Explore GIS processing and learn to work with various tools and libraries in Python. About This Book ? Analyze and process geospatial data using Python libraries such as; Anaconda, GeoPandas ? Leverage new ArcGIS API to process geospatial data for the cloud. ? Explore various Python geospatial web and machine learning frameworks. Who This Book Is For The audience for this book includes students, developers, and geospatial professionals who need a reference book that covers GIS data management, analysis, and automation techniques with code libraries built in Python 3. What You Will Learn ? Manage code libraries and abstract geospatial analysis techniques using Python 3. ? Explore popular code libraries that perform specific tasks for geospatial analysis. ? Utilize code libraries for data conversion, data management, web maps, and REST API creation. ? Learn techniques related to processing geospatial data in the cloud. ? Leverage features of Python 3 with geospatial databases such as PostGIS, SQL Server, and SpatiaLite. In Detail Python comes with a host of open source libraries and tools that help you work on professional geoprocessing tasks without investing in expensive tools. This book will introduce Python developers, both new and experienced, to a variety of new code libraries that have been developed to perform geospatial analysis, statistical analysis, and data management. This book will use examples and code snippets that will help explain how Python 3 differs from Python 2, and how these new code libraries can be used to solve age-old problems in geospatial analysis. You will begin by understanding what geoprocessing is and explore the tools and libraries that Python 3 offers. You will then learn to use Python code libraries to read and write geospatial data. You will then learn to perform geospatial queries within databases and learn PyQGIS to automate analysis within the QGIS mapping suite. Moving forward, you will explore the newly released ArcGIS API for Python and ArcGIS Online to perform geospatial analysis and create ArcGIS Online web maps. Further, you will deep dive into Python Geospatial web frameworks and learn to create a geospatial REST API. Style and approach The book takes a practical, example-driven approach to teach you GIS analysis and automation techniques with Python 3.

Building efficient Python applications at minimal cost by adopting serverless architectures About This Book ? Design and set up a data flow between cloud services and custom business logic ? Make your applications efficient and reliable using serverless architecture ? Build and deploy scalable serverless Python APIs Who This Book Is For This book is for Python developers who would like to learn about serverless architecture. Python programming knowledge is assumed. What You Will Learn ? Understand how AWS Lambda and Microsoft Azure Functions work and use them to create an application ? Explore various triggers and how to select them, based on the problem statement ? Build deployment packages for Lambda functions ? Master the finer details about building Lambda functions and versioning ? Log and monitor serverless applications ? Learn about security in AWS and Lambda functions ? Scale up serverless applications to handle huge workloads and serverless distributed systems in production ? Understand SAM model deployment in AWS Lambda In Detail Serverless architectures allow you to build and run applications and services without having to manage the infrastructure. Many companies have adopted this architecture to save cost and improve scalability. This book will help you design serverless architectures for your applications with AWS and Python. The book is divided into three modules. The first module explains the fundamentals of serverless architecture and how AWS lambda functions work. In the next module, you will learn to build, release, and deploy your application to production. You will also learn to log and test your application. In the third module, we will take you through advanced topics such as building a serverless API for your application. You will also learn to troubleshoot and monitor your app and master AWS lambda programming concepts with API references. Moving on, you will also learn how to scale up serverless applications and handle distributed serverless systems in production. By the end of the book, you will be equipped with the knowledge required to build scalable and cost-efficient Python applications with a serverless framework. Style and approach The book takes a pragmatic approach, using a real-world example to demonstrate building efficient, secure, and scalable serverless applications.

Discover best practices and troubleshooting solutions when working on ROS About This Book ? Develop complex robotic applications using ROS to interface robot manipulators and mobile robots ? Gain insight into autonomous navigation in mobile robots and motion planning in robot manipulators ? Discover best practices and troubleshooting solutions Who This Book Is For If you are a robotics enthusiast or researcher who want to learn more about building robot applications using ROS, this book is for you. In order to learn from this book, you should have a basic knowledge of ROS, GNU/Linux, and C++ programming concepts. The book is also excellent for programmers who want to explore the advanced features of ROS. What You Will Learn ? Create a robot model with a seven-DOF robotic arm and a differential wheeled mobile robot ? Work with Gazebo and V-REP robotic simulator ? Implement autonomous navigation in differential drive robots using SLAM and AMCL packages ? Explore the ROS Pluginlib, ROS nodelets, and Gazebo plugins ? Interface I/O boards such as Arduino, robot sensors, and high-end actuators ? Simulate and motion plan an ABB and universal arm using ROS Industrial ? Explore the latest version of the ROS framework ? Work with the motion planning of a seven-DOF arm using MoveIt! In Detail In this day and age, robotics has been gaining a lot of traction in various industries where consistency and perfection matter. Automation is achieved via robotic applications and various platforms that support robotics. The Robot Operating System (ROS) is a modular software platform to develop generic robotic applications. This book focuses on the most stable release of ROS (Kinetic Kame), discusses advanced concepts, and effectively teaches you programming using ROS. We begin with aninformative overview of the ROS framework, which will give you a clear idea of how ROS works. During the course of this book, you’ll learn to build models of complex robots, and simulate and interface the robot using the ROS MoveIt! motion planning library and ROS navigation stacks. Learn to leverage several ROS packages to embrace your robot models. After covering robot manipulation and navigation, you’ll get to grips with the interfacing I/O boards, sensors, and actuators of ROS. Vision sensors are a key component of robots, and an entire chapter is dedicated to the vision sensor and image elaboration, its interface in ROS and programming. You’ll also understand the hardware interface and simulation of complex robots to ROS and ROS Industrial. At the end of this book, you’ll discover the best practices to follow when programming using ROS. Style and approach This is a simplified guide to help you learn and master advanced topics in ROS using hands-on examples.

Create succinct and expressive implementations with functional programming in Python About This Book ? Learn how to choose between imperative and functional approaches based on expressiveness, clarity, and performance ? Get familiar with complex concepts such as monads, concurrency, and immutability ? Apply functional Python to common Exploratory Data Analysis (EDA) programming problems Who This Book Is For This book is for Python developers who would like to perform Functional programming with Python. Python Programming knowledge is assumed. What You Will Learn ? Use Python's generator functions and generator expressions to work with collections in a non-strict (or lazy) manner ? Utilize Python library modules including itertools, functools, multiprocessing, and concurrent features to ensure efficient functional programs ? Use Python strings with object-oriented suffix notation and prefix notation ? Avoid stateful classes with families of tuples ? Design and implement decorators to create composite functions ? Use functions such as max(), min(), map(), filter(), and sorted() ? Write higher-order functions In Detail If you’re a Python developer who wants to discover how to take the power of functional programming (FP) and bring it into your own programs, then this book is essential for you, even if you know next to nothing about the paradigm. Starting with a general overview of functional concepts, you’ll explore common functional features such as first-class and higher-order functions, pure functions, and more. You’ll see how these are accomplished in Python 3.6 to give you the core foundations you’ll build upon. After that, you’ll discover common functional optimizations for Python to help your apps reach even higher speeds. You’ll learn FP concepts such as lazy evaluation using Python’s generator functions and expressions. Moving forward, you’ll learn to design and implement decorators to create composite functions. You'll also explore data preparation techniques and data exploration in depth, and see how the Python standard library fits the functional programming model. Finally, to top off your journey into the world of functional Python, you’ll at look at the PyMonad project and some larger examples to put everything into perspective. Style and approach This book provides a general overview of functional concepts and then delves deeper into the functional features, showing you how the Python standard library fits the functional programming model. It also demonstrates how to implement common functional programming design patterns and techniques in Python.

Learn to leverage the power of PowerCLI to automate your VMware vSphere environment with ease About This Book This is first book on the market that will enlighten you on the latest version of PowerCLI and how to implement it Effectively manage virtual machines, networks, and reports with the latest features of PowerCLI A comprehensive and practical book on automating VMware vSphere Who This Book Is For This book is ideal for you if you want to learn how to automate your VMware vSphere or vCloud infrastructure by getting the most out of PowerCLI. It’s assumed that you have some experience in administrating a vSphere or vCloud environment. Knowledge of Microsoft’s Windows PowerShell is not a prerequisite. What You Will Learn Explore PowerShell and PowerCLI cmdlets and their output objects See how to manage virtual machines and work with virtual networks Manage vCloud Director from PowerCLI Use Site Recovery Manager from PowerCLI to create a disaster recovery solution Manage NSX and vRealize Automation using REST API with PowerCLI Create and configure vSphere HA and DRS clusters Use vSphere Update Manager with PowerCLI to create patch baselines and scan hosts Explore reporting techniques to retrieve log files In Detail VMware vSphere PowerCLI, a free extension to Microsoft Windows PowerShell, enables you to automate the management of a VMware vSphere or vCloud environment. This book will show you how to automate your tasks and make your job easier. Starting with an introduction to the basics of PowerCLI, the book will teach you how to manage your vSphere and vCloud infrastructure from the command line. To help you manage a vSphere host overall, you will learn how to manage vSphere ESXi hosts, host profiles, host services, host firewall, and deploy and upgrade ESXi hosts using Image Builder and Auto Deploy. The next chapter will not only teach you how to create datastore and datastore clusters, but you’ll also work with profile-driven and policy-based storage to manage your storage. To create a disaster recovery solution and retrieve information from vRealize Operations, you will learn how to use Site Recovery Manager and vRealize Operations respectively. Towards the end, you’ll see how to use the REST APIs from PowerShell to manage NSX and vRealize Automation and create patch baselines, scan hosts against the baselines for missing patches, and re-mediate hosts. By the end of the book, you will be capable of using the best tool to automate the management and configuration of VMware vSphere. Style and approach This comprehensive book will teach system administrators everything about PowerCLI 6 and how to utilize it to automate VMware vSphere.

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.

Explore the latest features of Unity 2018 to create immersive VR projects for Oculus Rift, HTC Vive, Daydream and Gear VR About This Book ? A project-based guide to teach you how to develop immersive and fun VR applications using Unity 3D ? Build experiences with interactable objects, physics, UI, animations, C# scripting, and other Unity features ? Explore the world of VR by building experiences such as diorama, first-person characters, 360-degree projections, social VR, audio fireball game, and VR storytelling Who This Book Is For If you're a non-programmer unfamiliar with 3D computer graphics, or experienced in both but new to virtual reality, and are interested in building your own VR games or applications, then this book is for you. Any experience in Unity is an advantage. What You Will Learn ? Create 3D scenes with Unity and other 3D tools while learning about world space and scale ? Build and run VR applications for specific headsets, including Oculus, Vive, and Daydream ? Interact with virtual objects using eye gaze, hand controllers, and user input events ? Move around your VR scenes using locomotion and teleportation ? Implement an audio fireball game using physics and particle systems ? Implement an art gallery tour with teleportation and data info ? Design and build a VR storytelling animation with a soundtrack and timelines ? Create social VR experiences with Unity networking In Detail Unity has become the leading platform for building virtual reality games, applications, and experiences for this new generation of consumer VR devices. Unity Virtual Reality Projects walks you through a series of hands-on tutorials and in-depth discussions on using the Unity game engine. With its practical and project-based approach, this book will get you up to speed with the specifics of Virtual Reality development in Unity. You will learn how to use Unity to develop VR applications that can be experienced with devices such as Oculus, Daydream, and Vive. Among the many topics and projects, you will explore gaze-based versus hand controller input, world space UI canvases, locomotion and teleportation, software design patterns, 360-degree media, timeline animation, and multiplayer networking. You will learn the Unity 3D game engine via the interactive Unity Editor as well as C# programming. By the end of the book, you will be fully equipped to develop rich, interactive virtual reality experiences using Unity. Style and approach A practical step-by-step guide to building impressive VR experiences with Unity 2018.

This book will teach the concepts of test driven development in Java so you can build clean, maintainable and robust code About This Book ? Explore the most popular TDD tools and frameworks and become more proficient in building applications ? Create applications with better code design, fewer bugs, and higher test coverage, enabling you to get them to market quickly ? Implement test-driven programming methods into your development workflows Who This Book Is For If you're an experienced Java developer and want to implement more effective methods of programming systems and applications, then this book is for you. What You Will Learn ? Explore the tools and frameworks required for effective TDD development ? Perform the Red-Green-Refactor process efficiently, the pillar around which all other TDD procedures are based ? Master effective unit testing in isolation from the rest of your code ? Design simple and easily maintainable code by implementing different techniques ? Use mocking frameworks and techniques to easily write and quickly execute tests ? Develop an application to implement behavior-driven development in conjunction with unit testing ? Enable and disable features using feature toggles In Detail Test-driven development (TDD) is a development approach that relies on a test-first procedure that emphasizes writing a test before writing the necessary code, and then refactoring the code to optimize it.The value of performing TDD with Java, one of the longest established programming languages, is to improve the productivity of programmers and the maintainability and performance of code, and develop a deeper understanding of the language and how to employ it effectively. Starting with the basics of TDD and understanding why its adoption is beneficial, this book will take you from the first steps of TDD with Java until you are confident enough to embrace the practice in your day-to-day routine.You'll be guided through setting up tools, frameworks, and the environment you need, and we will dive right into hands-on exercises with the goal of mastering one practice, tool, or framework at a time. You'll learn about the Red-Green-Refactor procedure, how to write unit tests, and how to use them as executable documentation.With this book, you'll also discover how to design simple and easily maintainable code, work with mocks, utilize behavior-driven development, refactor old legacy code, and release a half-finished feature to production with feature toggles.You will finish this book with a deep understanding of the test-driven development methodology and the confidence to apply it to application programming with Java. Style and approach An easy-to-follow, hands-on guide to building applications through effective coding practices. This book covers practical examples by introducing different problems, each one designed as a learning exercise to help you understand each aspect of TDD.

Design RPA solutions to perform a wide range of transactional tasks with minimal cost and maximum ROI About This Book ? A beginner's guide to learn Robotic Process Automation and its impact on the modern world ? Design, test, and perform enterprise automation task with UiPath ? Create Automation apps and deploy them to all the computers in your department. Who This Book Is For If you would like to pursue a career in Robotic Process Automation or improve the efficiency of your businesses by automating common tasks, then this book is perfect for you. Prior programming knowledge of either Visual Basic or C# will be useful. What You Will Learn ? Understand Robotic Process Automation technology ? Learn UiPath programming techniques to deploy robot configurations ? Explore various data extraction techniques ? Learn about integrations with various popular applications such as SAP and MS Office ? Debug a programmed robot including logging and exception handling ? Maintain code version and source control ? Deploy and control Bots with UiPath Orchestrator In Detail Robotic Process Automation (RPA) enables automating business processes using software robots. Software robots interpret, trigger responses, and communicate with other systems just like humans do. Robotic processes and intelligent automation tools can help businesses improve the effectiveness of services faster and at a lower cost than current methods. This book is the perfect start to your automation journey, with a special focus on one of the most popular RPA tools: UiPath. Learning Robotic Process Automation takes you on a journey from understanding the basics of RPA to advanced implementation techniques. You will become oriented in the UiPath interface and learn about its workflow. Once you are familiar with the environment, we will get hands-on with automating different applications such as Excel, SAP, Windows and web applications, screen and web scraping, working with user events, as well as understanding exceptions and debugging. By the end of the book, you'll not only be able to build your first software bot, but also you'll wire it to perform various automation tasks with the help of best practices for bot deployment. Style and approach This book will help you kick-start your automation journey with a special focus on one of the most popular RPA tools: UiPath.

Enhance your Kotlin programming skills by building 3 real-world applications About This Book ? Build three full-fledged, engaging applications from scratch and learn to deploy them ? Enhance your app development and programming activities with Kotlin’s powerful and intuitive tools and utilities. ? Experience the gentle learning curve, expressiveness, and intuitiveness of Kotlin, as you develop your own applications Who This Book Is For This book is for those who are new to Kotlin or are familiar with the basics, having dabbled with Java until now. Basic programming knowledge is mandatory. What You Will Learn ? Learn the building blocks of the Kotlin programming language ? Develop powerful RESTful microservices for Android applications ? Create reactive Android applications efficiently ? Implement an MVC architecture pattern and dependency management using Kotlin ? Centralize, transform, and stash data with Logstash ? Secure applications using Spring Security ? Deploy Kotlin microservices to AWS and Android applications to the Play Store In Detail Kotlin greatly reduces the verbosity of source code. With Google having announced their support for Kotlin as a first-class language for writing Android apps, now's the time learn how to create apps from scratch with Kotlin Kotlin Programming By Example takes you through the building blocks of Kotlin, such as functions and classes. You’ll explore various features of Kotlin by building three applications of varying complexity. For a quick start to Android development, we look at building a classic game, Tetris, and elaborate on object-oriented programming in Kotlin. Our next application will be a messenger app, a level up in terms of complexity. Before moving onto the third app, we take a look at data persistent methods, helping us learn about the storage and retrieval of useful applications. Our final app is a place reviewer: a web application that will make use of the Google Maps API and Place Picker. By the end of this book, you will have gained experience of of creating and deploying Android applications using Kotlin. Style and approach Here we will build three exciting projects in Kotlin which will demonstrate how to effectively use Kotlin language constructs

Create succinct and expressive implementations with functional programming in Python About This Book ? Learn how to choose between imperative and functional approaches based on expressiveness, clarity, and performance ? Get familiar with complex concepts such as monads, concurrency, and immutability ? Apply functional Python to common Exploratory Data Analysis (EDA) programming problems Who This Book Is For This book is for Python developers who would like to perform Functional programming with Python. Python Programming knowledge is assumed. What You Will Learn ? Use Python's generator functions and generator expressions to work with collections in a non-strict (or lazy) manner ? Utilize Python library modules including itertools, functools, multiprocessing, and concurrent features to ensure efficient functional programs ? Use Python strings with object-oriented suffix notation and prefix notation ? Avoid stateful classes with families of tuples ? Design and implement decorators to create composite functions ? Use functions such as max(), min(), map(), filter(), and sorted() ? Write higher-order functions In Detail If you’re a Python developer who wants to discover how to take the power of functional programming (FP) and bring it into your own programs, then this book is essential for you, even if you know next to nothing about the paradigm. Starting with a general overview of functional concepts, you’ll explore common functional features such as first-class and higher-order functions, pure functions, and more. You’ll see how these are accomplished in Python 3.6 to give you the core foundations you’ll build upon. After that, you’ll discover common functional optimizations for Python to help your apps reach even higher speeds. You’ll learn FP concepts such as lazy evaluation using Python’s generator functions and expressions. Moving forward, you’ll learn to design and implement decorators to create composite functions. You'll also explore data preparation techniques and data exploration in depth, and see how the Python standard library fits the functional programming model. Finally, to top off your journey into the world of functional Python, you’ll at look at the PyMonad project and some larger examples to put everything into perspective. Style and approach This book provides a general overview of functional concepts and then delves deeper into the functional features, showing you how the Python standard library fits the functional programming model. It also demonstrates how to implement common functional programming design patterns and techniques in Python.