Create powerful, effective visualizations to help analyze your data with Tableau 10 by your side About This Book Cook your favorite Tableau 10 business intelligence recipe with the help of this easy-to-follow book Build beautiful, interactive dashboards and visualizations in Tableau 10 that help you make informed decisions This rich collection of independent recipes cover everything needed to become an advanced Tableau user and get an edge over other Tableau users Who This Book Is For This book is targeted to business, data, and analytics professionals who want to build rich interactive visualizations using Tableau. Familiarity with previous versions of Tableau would be helpful, but is not necessary. What You Will Learn Become familiar with the Tableau interface Build basic to more advanced charts with step-by-step recipes Use filters, calculated fields, parameters, and actions to add interactivity to charts and dashboards Prepare and transform data for analysis using Tableau’s built-in tools and functions Create effective and compelling dashboards and story points Leverage Tableau’s mapping capabilities to visualize location and shape data Integrate analytics and forecasting to enhance data analysis Get to know tips and tricks to work more quickly and effectively in Tableau Increase your confidence and competence in creating rich, interactive visualizations in Tableau In Detail Tableau is a software tool that can speed up data analysis through its rich visualization capabilities, and help uncover insights for better and smarter decision making. This book is for the business, technology, data and analytics professionals who use and analyze data and data-driven approaches to support business operations and strategic initiatives in their organizations. This book provides easy-to-follow recipes to get the reader up and running with Tableau 10, and covers basic to advanced use cases and scenarios. The book starts with building basic charts in Tableau and moves on to building more complex charts by incorporating different Tableau features and interactivity components. There is an entire chapter dedicated to dashboard techniques and best practices. A number of recipes specifically for geospatial visualization, analytics, and data preparation are also covered. By the end of this book, you’ll have gained confidence and competence to analyze and communicate data and insights more efficiently and effectively by creating compelling interactive charts, dashboards, and stories in Tableau. Style and approach This book is a collection of independent recipes that cover a wide range of options for data visualization on offer with Tableau. With the help of the recipes in this book, you can explore Tableau and pick the business intelligence solution that’s best suited for your needs.

Design and implement successful private clouds with OpenStack About This Book Explore the various design choices available for cloud architects within an OpenStack deployment Craft an OpenStack architecture and deployment pipeline to meet the unique needs of your organization Create a product roadmap for Infrastructure as a Service in your organization using this hands-on guide Who This Book Is For This book is written especially for those who will design OpenStack clouds and lead their implementation. These people are typically cloud architects, but may also be in product management, systems engineering, or enterprise architecture. What You Will Learn Familiarize yourself with the components of OpenStack Build an increasingly complex OpenStack lab deployment Write compelling documentation for the architecture teams within your organization Apply Agile configuration management techniques to deploy OpenStack Integrate OpenStack with your organization's identity management, provisioning, and billing systems Configure a robust virtual environment for users to interact with Use enterprise security guidelines for your OpenStack deployment Create a product roadmap that delivers functionality quickly to the users of your platform In Detail Over the last five years, hundreds of organizations have successfully implemented Infrastructure as a Service (IaaS) platforms based on OpenStack. The huge amount of investment from these organizations, industry giants such as IBM and HP, as well as open source leaders such as Red Hat have led analysts to label OpenStack as the most important open source technology since the Linux operating system. Because of its ambitious scope, OpenStack is a complex and fast-evolving open source project that requires a diverse skill-set to design and implement it. This guide leads you through each of the major decision points that you'll face while architecting an OpenStack private cloud for your organization. At each point, we offer you advice based on the experience we've gained from designing and leading successful OpenStack projects in a wide range of industries. Each chapter also includes lab material that gives you a chance to install and configure the technologies used to build production-quality OpenStack clouds. Most importantly, we focus on ensuring that your OpenStack project meets the needs of your organization, which will guarantee a successful rollout. Style and approach This is practical, hands-on guide to implementing OpenStack clouds, where each topic is illustrated with real-world examples and then the technical points are proven in the lab.

Build a tower defense game and earn delectable C# treats by baking cupcakes and fighting fearsome sweet-toothed pandas About This Book Build a complete and exciting 2D Tower Defense game from scratch. Understand and learn to perform each phase of the game development pipeline Homework and exercises to improve your skills and take them to the next level Who This Book Is For If you are looking forward to get started with 2D game development, either if you are a newcomer to this world, or you came from 3D games or other game engines, this book is for you. Although there are many references to other resources throughout the book, it is assumed that you have a general understanding of C# and its syntax and structure. What You Will Learn Import and set up assets for 2D game development Design and implement dynamic and responsive User Interfaces Create and handle complex animation systems Unlock all the potentiality of the physics engine Implement Artificial Intelligence algorithms to give intelligence to your NPCs Script gameplay and overall bring your ideas to life In Detail Want to get started in the world of 2D game development with UnityThis book will take your hand and guide you through this amazing journey to let you know exactly what you need to build the games you want to build, without sacrificing quality. You will build a solid understanding of Unity 5.x, by focusing with the embedded tools to develop 2D games. In learning about these, along with accurate explanations and practical examples, you will design, develop, learn how to market and publish a delectable Tower Defense game about cupcakes versus pandas. Each chapter in this book is structured to give you a full understanding on a specific aspect of the workflow pipeline. Each of these aspects are essential for developing games in Unity. In a step-by-step approach, you will learn about each of the following phases: Game Design, Asset Importing, Scripting, User Interfaces, Animations, Physics, Artificial Intelligence, Gameplay Programming, Polishing and Improving, Marketing, Publishing and much more. This book provides you with exercises and homework at the end of each chapter so that you can level up your skills as a Unity game developer. In addition, each of these parts are centered on a common point of discussion with other learners just like you. Therefore, by sharing your ideas with other people you will not only develop your skills but you will also build a network. Style and approach This is a fun step-by-step approach in the whole pipeline of 2D game development in Unity, which is explained in a conversational and easy-to-follow style. Each topic is explained sequentially, allowing you to experience both basics and advanced features of Unity. By doing this, the book is able to provide you with a solid grasp on each of the topics. In this way, by engaging with the book’s content, exploring the additional references to further readings and completing the homework sections, you are able to challenge yourself and apply what you know in a variety of ways. Once you have finished reading this book, you will be well on your way to developing games from start to finish!

Exploit the visualization capabilities of Kibana and build powerful interactive dashboards About This Book Introduction to data-driven architecture and the Elastic stack Build effective dashboards for data visualization and explore datasets with Elastic Graph A comprehensive guide to learning scalable data visualization techniques in Kibana Who This Book Is For If you are a developer, data visualization engineer, or data scientist who wants to get the best of data visualization at scale then this book is perfect for you. A basic understanding of Elasticsearch and Logstash is required to make the best use of this book. What You Will Learn How to create visualizations in Kibana Ingest log data, structure an Elasticsearch cluster, and create visualization assets in Kibana Embed Kibana visualization on web pages Scaffold, develop, and deploy new Kibana & Timelion customizations Build a metrics dashboard in Timelion based on time series data Use the Graph plugin visualization feature and leverage a graph query Create, implement, package, and deploy a new custom plugin Use Prelert to solve anomaly detection challenges In Detail Kibana is an open source data visualization platform that allows you to interact with your data through stunning, powerful graphics. Its simple, browser-based interface enables you to quickly create and share dynamic dashboards that display changes to Elasticsearch queries in real time. In this book, you’ll learn how to use the Elastic stack on top of a data architecture to visualize data in real time. All data architectures have different requirements and expectations when it comes to visualizing the data, whether it’s logging analytics, metrics, business analytics, graph analytics, or scaling them as per your business requirements. This book will help you master Elastic visualization tools and adapt them to the requirements of your project. You will start by learning how to use the basic visualization features of Kibana 5. Then you will be shown how to implement a pure metric analytics architecture and visualize it using Timelion, a very recent and trendy feature of the Elastic stack. You will learn how to correlate data using the brand-new Graph visualization and build relationships between documents. Finally, you will be familiarized with the setup of a Kibana development environment so that you can build a custom Kibana plugin. By the end of this book you will have all the information needed to take your Elastic stack skills to a new level of data visualization. Style and approach This book takes a comprehensive, step-by-step approach to working with the visualization aspects of the Elastic stack. Every concept is presented in a very easy-to-follow manner that shows you both the logic and method of implementation. Real world cases are referenced to highlight how each of the key concepts can be put to practical use.

Build, implement and scale distributed deep learning models for large-scale datasets About This Book Get to grips with the deep learning concepts and set up Hadoop to put them to use Implement and parallelize deep learning models on Hadoop’s YARN framework A comprehensive tutorial to distributed deep learning with Hadoop Who This Book Is For If you are a data scientist who wants to learn how to perform deep learning on Hadoop, this is the book for you. Knowledge of the basic machine learning concepts and some understanding of Hadoop is required to make the best use of this book. What You Will Learn Explore Deep Learning and various models associated with it Understand the challenges of implementing distributed deep learning with Hadoop and how to overcome it Implement Convolutional Neural Network (CNN) with deeplearning4j Delve into the implementation of Restricted Boltzmann Machines (RBM) Understand the mathematical explanation for implementing Recurrent Neural Networks (RNN) Get hands on practice of deep learning and their implementation with Hadoop. In Detail This book will teach you how to deploy large-scale dataset in deep neural networks with Hadoop for optimal performance. Starting with understanding what deep learning is, and what the various models associated with deep neural networks are, this book will then show you how to set up the Hadoop environment for deep learning. In this book, you will also learn how to overcome the challenges that you face while implementing distributed deep learning with large-scale unstructured datasets. The book will also show you how you can implement and parallelize the widely used deep learning models such as Deep Belief Networks, Convolutional Neural Networks, Recurrent Neural Networks, Restricted Boltzmann Machines and autoencoder using the popular deep learning library deeplearning4j. Get in-depth mathematical explanations and visual representations to help you understand the design and implementations of Recurrent Neural network and Denoising AutoEncoders with deeplearning4j. To give you a more practical perspective, the book will also teach you the implementation of large-scale video processing, image processing and natural language processing on Hadoop. By the end of this book, you will know how to deploy various deep neural networks in distributed systems using Hadoop. Style and approach This book takes a comprehensive, step-by-step approach to implement efficient deep learning models on Hadoop. It starts from the basics and builds the readers’ knowledge as they strengthen their understanding of the concepts. Practical examples are included in every step of the way to supplement the theory.

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.

Discover over 100 practical recipes to help you master the art of IT service management for your organization About This Book Unleash the capabilities of Microsoft System Center 2016 Service Manager Master the skills of configuring, deploying, managing, and troubleshooting your Service Manager 2016 This book contains practical recipes that leverage the key and newly added features and functionalities of Microsoft System Center 2016 Service Manager Who This Book Is For This book will be useful to IT professionals including SCSM administrators who want to configure and administer System Center Service Manager 2016 and understand how to solve specific problems and scenarios that arise. It will also be useful to users of Service Manager 2012 who want to learn about the new features and capabilities of the Service Manager 2016 release. It will be ideal if you have Service Manager experience as well as experience with other System Center products. What You Will Learn See a practical implementation of the ITSM framework and processes based on ITIL Deploy and configure the new Service Manager HTML5 Self-Service Portal along with Service Catalog design and configuration Get to know about Incident, Problem, and Change Management processes and configuration Get to grips with performing advanced personalization in Service Manager Discover how to set up and use automation with and within Service Manager 2016 Work with Service Manager Data Warehouse Find out what Security Roles are and how to implement them Learn how to upgrade from SCSM 2012 R2 to SCSM 2016 In Detail System Center Service Manager (SCSM) is an integrated platform that offers a simplified data center management experience by implementing best practices such as Incident Management, Service Request, and Change Control to achieve efficient service delivery across your organization. This book provides you with real-world recipes that can be used immediately and will show you how to configure and administer SCSM 2016. You’ll also find out how to solve particular problems and scenarios to take this tool further. You’ll start with recipes on implementing ITSM frameworks and processes and configuring Service Level Agreements (SLAs). Then, you'll work through deploying and configuring the HTML5 Self-Service Portal, configuring Incident and Problem Management, and designing and configuring Change and Release Management. You'll also learn about security roles and overall Microsoft SCSM 2016 administration. Toward the end of the book, we’ll look at advanced topics, such as presenting the wealth of information stored within the Service Manager Data Warehouse, standardizing SCSM deployments, and implementing automation. Style and approach This book will enlighten you on Microsoft System Center 2016 Service Manager through recipes that can be implemented directly in any enterprise. You can read the book from start to end if you’re a beginner, or just open up any chapter and start following the recipes as a reference for advanced users. This book consists of a pool of step-by-step recipes on how to perform activities in Service Manager.

Discover what it means to be an expert developer by exploring the latest features available to you in Alfresco One 5.x About This Book Create reliable and secure enterprise apps with the latest Alfresco One 5.x platform Explore all the latest Alfresco One 5.x APIs such as the CMIS API, Alfresco One API, and the integrated RESTful API to get more out of your enterprise apps Unleash the power of the latest JavaScript engine and the JavaScript API for Alfresco to customize your existing apps for the Alfresco 5 platform Who This Book Is For If you’re an enterprise app developer who wants to create custom applications with Alfresco, then this book is for you. Previous knowledge with Alfresco would be helpful but is not necessary. What You Will Learn Create and manage a custom content model Configure the Alfresco Share user interface Build a new AngularJS 2.0 application Create business process definitions using Activiti Designer Discover the most common extensions provided by Alfresco Configure Alfresco to authenticate against LDAP, including & chaining" LDAP with Alfresco authentication Get familiar with the latest features of Alfresco Mobile SDK, Smart Search, and the new Angular framework In Detail Do you want to create more reliable and secure solutions for enterprise appsAlfresco One 5.x is your gateway to developing the best industry-standard enterprise apps and this book will help you to become a pro with Alfresco One 5.x development. This book will help you create a complete fully featured app for your organization and while you create that perfect app, you will explore and implement the new and intriguing features of Alfresco. The book starts with an introduction to the Alfresco platform and you’ll see how to configure and customize it. You will learn how to work with the content in a content management system and how you can extend it to your own use case. Next, you will find out how to work with Alfresco Share, an all-purpose user interface for general document management, and customize it. Moving on, you write web *s that create, read, and delete data in the back-end repository. Further on from that, you’ll work with a set of tools that Alfresco provides; to generate a basic AnglularJS application supporting use cases, to name a few authentication, document list, document view. Finally, you’ll learn how to develop your own Alfresco Mobile app and understand how Smart Folders and Search manager work. By the end of the book, you’ll know how to configure Alfresco to authenticate against LDAP, be able to set up Single Sign-On (SSO), and work with Alfresco’s security services. Style and approach This book takes a step-by-step practical tutorial-style approach helping you create a complete enterprise app using Alfresco.

Build data-intensive applications locally and deploy at scale using the combined powers of Python and Spark 2.0 About This Book Learn why and how you can efficiently use Python to process data and build machine learning models in Apache Spark 2.0 Develop and deploy efficient, scalable real-time Spark solutions Take your understanding of using Spark with Python to the next level with this jump start guide Who This Book Is For If you are a Python developer who wants to learn about the Apache Spark 2.0 ecosystem, this book is for you. A firm understanding of Python is expected to get the best out of the book. Familiarity with Spark would be useful, but is not mandatory. What You Will Learn Learn about Apache Spark and the Spark 2.0 architecture Build and interact with Spark DataFrames using Spark SQL Learn how to solve graph and deep learning problems using GraphFrames and TensorFrames respectively Read, transform, and understand data and use it to train machine learning models Build machine learning models with MLlib and ML Learn how to submit your applications programmatically using spark-submit Deploy locally built applications to a cluster In Detail Apache Spark is an open source framework for efficient cluster computing with a strong interface for data parallelism and fault tolerance. This book will show you how to leverage the power of Python and put it to use in the Spark ecosystem. You will start by getting a firm understanding of the Spark 2.0 architecture and how to set up a Python environment for Spark. You will get familiar with the modules available in PySpark. You will learn how to abstract data with RDDs and DataFrames and understand the streaming capabilities of PySpark. Also, you will get a thorough overview of machine learning capabilities of PySpark using ML and MLlib, graph processing using GraphFrames, and polyglot persistence using Blaze. Finally, you will learn how to deploy your applications to the cloud using the spark-submit command. By the end of this book, you will have established a firm understanding of the Spark Python API and how it can be used to build data-intensive applications. Style and approach This book takes a very comprehensive, step-by-step approach so you understand how the Spark ecosystem can be used with Python to develop efficient, scalable solutions. Every chapter is standalone and written in a very easy-to-understand manner, with a focus on both the hows and the whys of each concept.

Discover over 65 recipes to help you create breathtaking data visualizations using the latest features of D3 About This Book Learn about D3 4.0 from the inside out and master its new features Utilize D3 packages to generate graphs, manipulate data, and create beautiful presentations Solve real-world visualization problems with the help of practical recipes Who This Book Is For If you are a developer familiar with HTML, CSS, and JavaScript, and you wish to get the most out of D3, then this book is for you. This book can serve as a desktop quick-reference guide for experienced data visualization developers. You’ll also find this book useful if you’re a D3 user who wants to take advantage of the new features introduced in D3 4.0. You should have previous experience with D3. What You Will Learn Get a solid understanding of the D3 fundamentals and idioms Use D3 to load, manipulate, and map data to any kind of visual representation on the web Create data-driven dynamic visualizations that update as the data does Leverage the various modules provided by D3 to create sophisticated, dynamic, and interactive charts and graphics Create data-driven transitions and animations within your visualizations Understand and leverage more advanced concepts such as force, touch, and Geo data visualizations In Detail This book gives you all the guidance you need to start creating modern data visualizations with D3 4.x that take advantage of the latest capabilities of JavaScript. The book starts with the basic D3 structure and building blocks and quickly moves on to writing idiomatic D3-style JavaScript code. You will learn how to work with selection to target certain visual elements on the page, then you will see techniques to represent data both in programming constructs and its visual metaphor. You will learn how map values in your data domain to the visual domain using scales, and use the various shape functions supported by D3 to create SVG shapes in visualizations. Moving on, you’ll see how to use and customize various D3 axes and master transition to add bells and whistles to otherwise dry visualizations. You’ll also learn to work with charts, hierarchy, graphs, and build interactive visualizations. Next you’ll work with Force, which is one of the most awe-inspiring techniques you can add to your visualizations, and you’ll implement a fully functional Choropleth map (a special purpose colored map) in D3. Finally, you’ll learn to unit test data visualization code and test-driven development in a visualization project so you know how to produce high-quality D3 code. Style and approach This step-by-step guide to mastering data visualizations with D3 will help you create amazing data visualizations with professional efficiency and precision. It is a solution-based guide in which you learn through practical recipes, illustrations, and code samples.

Learn effective tools and techniques to separate big data into manageable and logical components for efficient data visualization About This Book This unique guide teaches you how to visualize your cluttered, huge amounts of big data with ease It is rich with ample options and solid use cases for big data visualization, and is a must-have book for your shelf Improve your decision-making by visualizing your big data the right way Who This Book Is For This book is for data analysts or those with a basic knowledge of big data analysis who want to learn big data visualization in order to make their analysis more useful. You need sufficient knowledge of big data platform tools such as Hadoop and also some experience with programming languages such as R. This book will be great for those who are familiar with conventional data visualizations and now want to widen their horizon by exploring big data visualizations. What You Will Learn Understand how basic analytics is affected by big data Deep dive into effective and efficient ways of visualizing big data Get to know various approaches (using various technologies) to address the challenges of visualizing big data Comprehend the concepts and models used to visualize big data Know how to visualize big data in real time and for different use cases Understand how to integrate popular dashboard visualization tools such as Splunk and Tableau Get to know the value and process of integrating visual big data with BI tools such as Tableau Make sense of the visualization options for big data, based upon the best suited visualization techniques for big data In Detail When it comes to big data, regular data visualization tools with basic features become insufficient. This book covers the concepts and models used to visualize big data, with a focus on efficient visualizations. This book works around big data visualizations and the challenges around visualizing big data and address characteristic challenges of visualizing like speed in accessing, understanding/adding context to, improving the quality of the data, displaying results, outliers, and so on. We focus on the most popular libraries to execute the tasks of big data visualization and explore "big data oriented" tools such as Hadoop and Tableau. We will show you how data changes with different variables and for different use cases with step-through topics such as: importing data to something like Hadoop, basic analytics. The choice of visualizations depends on the most suited techniques for big data, and we will show you the various options for big data visualizations based upon industry-proven techniques. You will then learn how to integrate popular visualization tools with graphing databases to see how huge amounts of certain data. Finally, you will find out how to display the integration of visual big data with BI using Cognos BI. Style and approach With the help of insightful real-world use cases, we’ll tackle data in the world of big data. The scalability and hugeness of the data makes big data visualizations different from normal data visualizations, and this book addresses all the difficulties encountered by professionals while visualizing their big data.

Over 50 practical and immediately applicable recipes to help you manage services in your enterprise environment efficiently About This Book Solve problems and challenges encountered while implementing or using ServiceNow in your organization Helps you build core administration, management, and maintenance skills to automate and orchestrate your IT environment Comes with recipes to improve the way you design and create automated workflows Who This Book Is For This book targets IT professionals and administrators who have some experience of working with ServiceNow already and are looking to solve regular or unique problems that surface when using ServiceNow. It’s advisable to have a basic level of administration experience with ServiceNow. Familiarity with JavaScript is assumed. What You Will Learn Grasp the basics, such as entering and navigation, required to implement ServiceNow Perform core configuration and management tasks Use the ServiceNow plugins to manage development Build and publish custom applications for service management Design data-driven apps to connect with outside worlds by getting into Client and server *ing Configure alerts and notifications and understand e-mail troubleshooting and watermarking Build and configure reports to set up your dashboard as per the requirement Create and configure workflow activities In Detail ServiceNow is the ideal platform for you to create enterprise-level applications, giving borh requesters and fulfillers better visibility and access to a process. With this title we’ll guide you through the world of ServiceNow, letting you take on the best the platform offers you with the least amount of hassle. Starting with the core configuration and management tasks, this book will help you build data-driven apps and it will also explore development best practices. You will learn to set up email notifications for users and work with the database view for reporting. Next, the book will guide you through creating various tasks from the workflow and show you how to make the most of the workflow utilities available in ServiceNow. Finally, the book will drive you through the auditing and diagnosing aspects of ServiceNow. By the end of this book, you will acquire immediately applicable skills to rectify everyday problems encountered on the ServiceNow platform. Style and approach This book follows a recipe-based problem-solution approach to address and dispel challenges faced when implementing and using ServiceNow on a regular basis. It will act as a quick solution when trying to solve specific problems without having to read an exhaustive tutorial.

Learn to build expert NLP and machine learning projects using NLTK and other Python libraries About This Book Break text down into its component parts for spelling correction, feature extraction, and phrase transformation Work through NLP concepts with simple and easy-to-follow programming recipes Gain insights into the current and budding research topics of NLP Who This Book Is For If you are an NLP or machine learning enthusiast and an intermediate Python programmer who wants to quickly master NLTK for natural language processing, then this Learning Path will do you a lot of good. Students of linguistics and semantic/sentiment analysis professionals will find it invaluable. What You Will Learn The scope of natural language complexity and how they are processed by machines Clean and wrangle text using tokenization and chunking to help you process data better Tokenize text into sentences and sentences into words Classify text and perform sentiment analysis Implement string matching algorithms and normalization techniques Understand and implement the concepts of information retrieval and text summarization Find out how to implement various NLP tasks in Python In Detail Natural Language Processing is a field of computational linguistics and artificial intelligence that deals with human-computer interaction. It provides a seamless interaction between computers and human beings and gives computers the ability to understand human speech with the help of machine learning. The number of human-computer interaction instances are increasing so it’s becoming imperative that computers comprehend all major natural languages. The first NLTK Essentials module is an introduction on how to build systems around NLP, with a focus on how to create a customized tokenizer and parser from scratch. You will learn essential concepts of NLP, be given practical insight into open source tool and libraries available in Python, shown how to analyze social media sites, and be given tools to deal with large scale text. This module also provides a workaround using some of the amazing capabilities of Python libraries such as NLTK, scikit-learn, pandas, and NumPy. The second Python 3 Text Processing with NLTK 3 Cookbook module teaches you the essential techniques of text and language processing with simple, straightforward examples. This includes organizing text corpora, creating your own custom corpus, text classification with a focus on sentiment analysis, and distributed text processing methods. The third Mastering Natural Language Processing with Python module will help you become an expert and assist you in creating your own NLP projects using NLTK. You will be guided through model development with machine learning tools, shown how to create training data, and given insight into the best practices for designing and building NLP-based applications using Python. This Learning Path combines some of the best that Packt has to offer in one complete, curated package and is designed to help you quickly learn text processing with Python and NLTK. It includes content from the following Packt products: NTLK essentials by Nitin Hardeniya Python 3 Text Processing with NLTK 3 Cookbook by Jacob Perkins Mastering Natural Language Processing with Python by Deepti Chopra, Nisheeth Joshi, and Iti Mathur Style and approach This comprehensive course creates a smooth learning path that teaches you how to get started with Natural Language Processing using Python and NLTK. You’ll learn to create effective NLP and machine learning projects using Python and NLTK.

Get to grips with 3D printing and learn to model designs using Blender About This Book From the author who brought you the first practical look at 3D printing with 3D Printing Blueprints Get a comprehensive coverage of the prototyping techniques you need to know to start printing your own 3D designs Rekindle your mathematical genius to design personalized objects for complex puzzles Who This Book Is For If you’re new to the world of 3D printing, this is the book for you. Some basic knowledge of Blender and geometry would be helpful, but is not necessary. What You Will Learn Get to know about the different types of 3D printers and their limitations See how Y, H, and T shapes illustrate different ideas of successful 3D design for home 3D printers Set up and configure Blender to model a file for 3D printing Understand material characteristics, printing specifications, tolerances, and design tips Work through the techniques of editing complex meshes, smoothing, combining shapes, and exporting them into STL files for printing Break down complex geometries into multiple simple shapes and model them in layers using Blender Design, manipulate, and export 3D models for 3D printing with Blender Master the art of creating meshes, scaling, subdivision, and adding detail with the Boolean modifier as well as sculpting a custom shape Cut a model into small pieces and understand how to design complex interlocking joints that form a part of a jigsaw puzzle In Detail 3D printing has revolutionized the way that global industries conceptualize and design products for mass consumption. Considered as the next “trillion-dollar” business, every industry is in the race to equip its personnel with techniques to prototype and simplify complex manufacturing process. This book will take you through some simple to complex and effective principles of designing 3D printed objects using Blender. There is a comprehensive coverage of projects such as a 3D print-ready octopus pencil holder, which will teach you how to add basic geometric shapes, and use techniques such as extruding and subdividing to transform these shapes into complex meshes. Furthermore, you’ll learn to use various techniques to derive measurements for an object, model these objects using Blender, organize the parts into layers, and later combine them to create the desired object with the help of a 3D printable SD card holder ring design project. The final project will help you master the techniques of designing simple to complex puzzles models for 3D printing. Through the course of the book, we'll explore various robust sculpting methods supported by Blender to create objects. You’ll move, rotate, and scale the object, and manipulate the view. You’ll edit objects with actions such as bends or curves, similar to drawing or building up a clay structure of different shapes and sizes. By the end of the book, you will have gained thorough practical hands-on experience to be able to create a real-world 3D printable object of your choice. Style and approach This is a hands-on guide to the world of 3D printing. With the help of simple to complex projects, you'll learn various techniques to design 3D printable objects using Blender.

Over 75 practical recipes to confidently design an efficient virtual datacenter with VMware vSphere 6.x About This Book Get the first book on the market that helps you design a virtualized data center with VMware vSphere 6 Achieve enhanced compute, storage, network, and management capabilities for your virtual data center Exciting and practical recipes help you to design a virtual data easily by leveraging the features of VMware vSphere 6 Who This Book Is For If you are an administrator or consultant interested in designing virtualized datacenter environments using VMware vSphere 6.x or previous versions of vSphere and the supporting components, this book is for you. It will help both new and experienced architects deliver professional VMware vSphere virtual datacenter designs. What You Will Learn Identify key factors related to a vSphere design and apply them to every step of the design process Mitigate security risks and meet compliance requirements in a vSphere design. Create a vSphere conceptual design by identifying technical and business requirements Determine the type of database to use based on the deployment size. Design for performance, availability, recoverability, manageability, and security Map the logical resource design into the physical vSphere design Create professional vSphere design documentation to ensure a successful implementation of the vSphere design Leverage the latest vSphere 6.x features to ensure manageability, performance, availability, and security in a virtual datacenter design In Detail VMware is the industry leader in data center virtualization. The vSphere 6.x suite of products provides a robust and resilient platform to virtualize server and application workloads. With the release of 6.x a whole range of new features has come along such as ESXi Security enhancements, fault tolerance, high availability enhancements, and virtual volumes, thus simplifying the secure management of resources, the availability of applications, and performance enhancements of workloads deployed in the virtualized datacenter. This book provides recipes to create a virtual datacenter design using the features of vSphere 6.x by guiding you through the process of identifying the design factors and applying them to the logical and physical design process. You’ll follow steps that walk you through the design process from beginning to end, right from the discovery process to creating the conceptual design; calculating the resource requirements of the logical storage, compute, and network design; mapping the logical requirements to a physical design; security design; and finally creating the design documentation. The recipes in this book provide guidance on making design decisions to ensure the successful creation, and ultimately the successful implementation, of a VMware vSphere 6.x virtual data center design. Style and Approach The book follows a recipe-based approach that consists of practical recipes to effectively design a virtual data center.

Master the art of building analytical models using R About This Book Load, wrangle, and analyze your data using the world's most powerful statistical programming language Build and customize publication-quality visualizations of powerful and stunning R graphs Develop key skills and techniques with R to create and customize data mining algorithms Use R to optimize your trading strategy and build up your own risk management system Discover how to build machine learning algorithms, prepare data, and dig deep into data prediction techniques with R Who This Book Is For This course is for data scientist or quantitative analyst who are looking at learning R and take advantage of its powerful analytical design framework. It’s a seamless journey in becoming a full-stack R developer. What You Will Learn Describe and visualize the behavior of data and relationships between data Gain a thorough understanding of statistical reasoning and sampling Handle missing data gracefully using multiple imputation Create diverse types of bar charts using the default R functions Familiarize yourself with algorithms written in R for spatial data mining, text mining, and so on Understand relationships between market factors and their impact on your portfolio Harness the power of R to build machine learning algorithms with real-world data science applications Learn specialized machine learning techniques for text mining, big data, and more In Detail The R learning path created for you has five connected modules, which are a mini-course in their own right. As you complete each one, you'll have gained key skills and be ready for the material in the next module! This course begins by looking at the Data Analysis with R module. This will help you navigate the R environment. You'll gain a thorough understanding of statistical reasoning and sampling. Finally, you'll be able to put best practices into effect to make your job easier and facilitate reproducibility. The second place to explore is R Graphs, which will help you leverage powerful default R graphics and utilize advanced graphics systems such as lattice and ggplot2, the grammar of graphics. You'll learn how to produce, customize, and publish advanced visualizations using this popular and powerful framework. With the third module, Learning Data Mining with R, you will learn how to manipulate data with R using code snippets and be introduced to mining frequent patterns, association, and correlations while working with R programs. The Mastering R for Quantitative Finance module pragmatically introduces both the quantitative finance concepts and their modeling in R, enabling you to build a tailor-made trading system on your own. By the end of the module, you will be well-versed with various financial techniques using R and will be able to place good bets while making financial decisions. Finally, we'll look at the Machine Learning with R module. With this module, you'll discover all the analytical tools you need to gain insights from complex data and learn how to choose the correct algorithm for your specific needs. You'll also learn to apply machine learning methods to deal with common tasks, including classification, prediction, forecasting, and so on. Style and approach Learn data analysis, data visualization techniques, data mining, and machine learning all using R and also learn to build models in quantitative finance using this powerful language.

Advance your skills in efficient data analysis and data processing using the powerful tools of Scala, Spark, and Hadoop About This Book This is a primer on functional-programming-style techniques to help you efficiently process and analyze all of your data Get acquainted with the best and newest tools available such as Scala, Spark, Parquet and MLlib for machine learning Learn the best practices to incorporate new Big Data machine learning in your data-driven enterprise to gain future scalability and maintainability Who This Book Is For Mastering Scala Machine Learning is intended for enthusiasts who want to plunge into the new pool of emerging techniques for machine learning. Some familiarity with standard statistical techniques is required. What You Will Learn Sharpen your functional programming skills in Scala using REPL Apply standard and advanced machine learning techniques using Scala Get acquainted with Big Data technologies and grasp why we need a functional approach to Big Data Discover new data structures, algorithms, approaches, and habits that will allow you to work effectively with large amounts of data Understand the principles of supervised and unsupervised learning in machine learning Work with unstructured data and serialize it using Kryo, Protobuf, Avro, and AvroParquet Construct reliable and robust data pipelines and manage data in a data-driven enterprise Implement scalable model monitoring and alerts with Scala In Detail Since the advent of object-oriented programming, new technologies related to Big Data are constantly popping up on the market. One such technology is Scala, which is considered to be a successor to Java in the area of Big Data by many, like Java was to C/C++ in the area of distributed programing. This book aims to take your knowledge to next level and help you impart that knowledge to build advanced applications such as social media mining, intelligent news portals, and more. After a quick refresher on functional programming concepts using REPL, you will see some practical examples of setting up the development environment and tinkering with data. We will then explore working with Spark and MLlib using k-means and decision trees. Most of the data that we produce today is unstructured and raw, and you will learn to tackle this type of data with advanced topics such as regression, classification, integration, and working with graph algorithms. Finally, you will discover at how to use Scala to perform complex concept analysis, to monitor model performance, and to build a model repository. By the end of this book, you will have gained expertise in performing Scala machine learning and will be able to build complex machine learning projects using Scala. Style and approach This hands-on guide dives straight into implementing Scala for machine learning without delving much into mathematical proofs or validations. There are ample code examples and tricks that will help you sail through using the standard techniques and libraries. This book provides practical examples from the field on how to correctly tackle data analysis problems, particularly for modern Big Data datasets.

A practical, indispensable security guide that will navigate you through the complex realm of securely building and deploying systems in our IoT-connected world About This Book Learn to design and implement cyber security strategies for your organization Learn to protect cyber-physical systems and utilize forensic data analysis to beat vulnerabilities in your IoT ecosystem Learn best practices to secure your data from device to the cloud Gain insight into privacy-enhancing techniques and technologies Who This Book Is For This book targets IT Security Professionals and Security Engineers (including pentesters, security architects and ethical hackers) who would like to ensure security of their organization's data when connected through the IoT. Business analysts and managers will also find it useful. What You Will Learn Learn how to break down cross-industry barriers by adopting the best practices for IoT deployments Build a rock-solid security program for IoT that is cost-effective and easy to maintain Demystify complex topics such as cryptography, privacy, and penetration testing to improve your security posture See how the selection of individual components can affect the security posture of the entire system Use Systems Security Engineering and Privacy-by-design principles to design a secure IoT ecosystem Get to know how to leverage the burdgening cloud-based systems that will support the IoT into the future. In Detail With the advent of Intenret of Things (IoT), businesses will be faced with defending against new types of threats. The business ecosystem now includes cloud computing infrastructure, mobile and fixed endpoints that open up new attack surfaces, a desire to share information with many stakeholders and a need to take action quickly based on large quantities of collected data. . It therefore becomes critical to ensure that cyber security threats are contained to a minimum when implementing new IoT services and solutions. . The interconnectivity of people, devices, and companies raises stakes to a new level as computing and action become even more mobile, everything becomes connected to the cloud, and infrastructure is strained to securely manage the billions of devices that will connect us all to the IoT. This book shows you how to implement cyber-security solutions, IoT design best practices and risk mitigation methodologies to address device and infrastructure threats to IoT solutions. This book will take readers on a journey that begins with understanding the IoT and how it can be applied in various industries, goes on to describe the security challenges associated with the IoT, and then provides a set of guidelines to architect and deploy a secure IoT in your Enterprise. The book will showcase how the IoT is implemented in early-adopting industries and describe how lessons can be learned and shared across diverse industries to support a secure IoT. Style and approach This book aims to educate readers on key areas in IoT security. It walks readers through engaging with security challenges and then provides answers on how to successfully manage IoT security and build a safe infrastructure for smart devices. After reading this book, you will understand the true potential of tools and solutions in order to build real-time security intelligence on IoT networks.

Become an expert at using Python for advanced statistical analysis of data using real-world examples About This Book Clean, format, and explore data using graphical and numerical summaries Leverage the IPython environment to efficiently analyze data with Python Packed with easy-to-follow examples to develop advanced computational skills for the analysis of complex data Who This Book Is For If you are a competent Python developer who wants to take your data analysis skills to the next level by solving complex problems, then this advanced guide is for you. Familiarity with the basics of applying Python libraries to data sets is assumed. What You Will Learn Read, sort, and map various data into Python and Pandas Recognise patterns so you can understand and explore data Use statistical models to discover patterns in data Review classical statistical inference using Python, Pandas, and SciPy Detect similarities and differences in data with clustering Clean your data to make it useful Work in Jupyter Notebook to produce publication ready figures to be included in reports In Detail Python, a multi-paradigm programming language, has become the language of choice for data scientists for data analysis, visualization, and machine learning. Ever imagined how to become an expert at effectively approaching data analysis problems, solving them, and extracting all of the available information from your dataWell, look no further, this is the book you want! Through this comprehensive guide, you will explore data and present results and conclusions from statistical analysis in a meaningful way. You’ll be able to quickly and accurately perform the hands-on sorting, reduction, and subsequent analysis, and fully appreciate how data analysis methods can support business decision-making. You’ll start off by learning about the tools available for data analysis in Python and will then explore the statistical models that are used to identify patterns in data. Gradually, you’ll move on to review statistical inference using Python, Pandas, and SciPy. After that, we’ll focus on performing regression using computational tools and you’ll get to understand the problem of identifying clusters in data in an algorithmic way. Finally, we delve into advanced techniques to quantify cause and effect using Bayesian methods and you’ll discover how to use Python’s tools for supervised machine learning. Style and approach This book takes a step-by-step approach to reading, processing, and analyzing data in Python using various methods and tools. Rich in examples, each topic connects to real-world examples and retrieves data directly online where possible. With this book, you are given the knowledge and tools to explore any data on your own, encouraging a curiosity befitting all data scientists.

Harness actionable insights from your data with computational statistics and simulations using R About This Book Learn five different simulation techniques (Monte Carlo, Discrete Event Simulation, System Dynamics, Agent-Based Modeling, and Resampling) in-depth using real-world case studies A unique book that teaches you the essential and fundamental concepts in statistical modeling and simulation Who This Book Is For This book is for users who are familiar with computational methods. If you want to learn about the advanced features of R, including the computer-intense Monte-Carlo methods as well as computational tools for statistical simulation, then this book is for you. Good knowledge of R programming is assumed/required. What You Will Learn The book aims to explore advanced R features to simulate data to extract insights from your data. Get to know the advanced features of R including high-performance computing and advanced data manipulation See random number simulation used to simulate distributions, data sets, and populations Simulate close-to-reality populations as the basis for agent-based micro-, model- and design-based simulations Applications to design statistical solutions with R for solving scientific and real world problems Comprehensive coverage of several R statistical packages like boot, simPop, VIM, data.table, dplyr, parallel, StatDA, simecol, simecolModels, deSolve and many more. In Detail Data Science with R aims to teach you how to begin performing data science tasks by taking advantage of Rs powerful ecosystem of packages. R being the most widely used programming language when used with data science can be a powerful combination to solve complexities involved with varied data sets in the real world. The book will provide a computational and methodological framework for statistical simulation to the users. Through this book, you will get in grips with the software environment R. After getting to know the background of popular methods in the area of computational statistics, you will see some applications in R to better understand the methods as well as gaining experience of working with real-world data and real-world problems. This book helps uncover the large-scale patterns in complex systems where interdependencies and variation are critical. An effective simulation is driven by data generating processes that accurately reflect real physical populations. You will learn how to plan and structure a simulation project to aid in the decision-making process as well as the presentation of results. By the end of this book, you reader will get in touch with the software environment R. After getting background on popular methods in the area, you will see applications in R to better understand the methods as well as to gain experience when working on real-world data and real-world problems. Style and approach This book takes a practical, hands-on approach to explain the statistical computing methods, gives advice on the usage of these methods, and provides computational tools to help you solve common problems in statistical simulation and computer-intense methods.

Arm yourself to make the most of the versatile, powerful Ubuntu Server with over 100 hands-on recipes About This Book Master the skills to setup secure and scalable web services with popular tools like Apache, Nginx, MySQL and HAProxy Set up your own cloud with Open Stack and quickly deploy applications with Docker or LXD Packed with clear, step-by-step recipes to let you protect you valuable data with your own chat servers, code hosting and collaboration tools. Who This Book Is For Ubuntu Server Cookbook is for system administrators or software developers with a basic understanding of the Linux operating system who want to set up their own servers. You are not required to have in-depth knowledge or hands-on experience with Ubuntu, but you should know the basics commands for directory navigation, file management, and the file editing tool. An understanding of computer networks is advisable What You Will Learn Set up high performance, scalable, and fault-tolerant back ends with web and database servers Facilitate team communication with a real-time chat service and collaboration tools Quickly deploy your applications to their own containers and scale your infrastructure as and when needed Find out how to set up your own cloud infrastructure for your internal use or rent it to the public Ensure quick and easy access for your users while also securing your infrastructure from intruders Set up a high performance private network with a personal VPN server and centralized authentication system Swiftly start a content streaming service Set up network storage for private data and source code and say good bye to costly and unreliable cloud services In Detail Ubuntu is one of the most secure operating systems and defines the highest level of security as compared other operating system. Ubuntu server is a popular Linux distribution and the first choice when deploying a Linux server. It can be used with a $35 Raspberry Pi to top-notch, thousand-dollar-per-month cloud hardware. Built with lists that there are 4 million + websites built using Ubuntu. With its easy-to-use package management tools and availability of well-known packages, we can quickly set up our own services such as web servers and database servers using Ubuntu. This book will help you develop the skills required to set up high performance and secure services with open source tools. Starting from user management and an in-depth look at networking, we then move on to cover the installation and management of web servers and database servers, as well as load balancing various services. You will quickly learn to set up your own cloud and minimize costs and efforts with application containers. Next, you will get to grips with setting up a secure real-time communication system. Finally, we’ll explore source code hosting and various collaboration tools. By the end of this book, you will be able to make the most of Ubuntu’s advanced functionalities. Style and approach This easy-to-follow guide contains a series of step-by-step recipes ranging from simple to complex. Each topic will start with basic introduction to each technology followed by a detailed step-by-step installation guide and then a detailed explanation of the approach taken during installation and the various advanced options available.