Use Wireshark 2 to overcome real-world network problems About This Book ? Delve into the core functionalities of the latest version of Wireshark ? Master network security skills with Wireshark 2 ? Efficiently find the root cause of network-related issues Who This Book Is For If you are a security professional or a network enthusiast and are interested in understanding the internal working of networks, and if you have some prior knowledge of using Wireshark, then this book is for you. What You Will Learn ? Understand what network and protocol analysis is and how it can help you ? Use Wireshark to capture packets in your network ? Filter captured traffic to only show what you need ? Explore useful statistic displays to make it easier to diagnose issues ? Customize Wireshark to your own specifications ? Analyze common network and network application protocols In Detail Wireshark, a combination of a Linux distro (Kali) and an open source security framework (Metasploit), is a popular and powerful tool. Wireshark is mainly used to analyze the bits and bytes that flow through a network. It efficiently deals with the second to the seventh layer of network protocols, and the analysis made is presented in a form that can be easily read by people. Mastering Wireshark 2 helps you gain expertise in securing your network. We start with installing and setting up Wireshark2.0, and then explore its interface in order to understand all of its functionalities. As you progress through the chapters, you will discover different ways to create, use, capture, and display filters. By halfway through the book, you will have mastered Wireshark features, analyzed different layers of the network protocol, and searched for anomalies. You’ll learn about plugins and APIs in depth. Finally, the book focuses on pocket analysis for security tasks, command-line utilities, and tools that manage trace files. By the end of the book, you'll have learned how to use Wireshark for network security analysis and configured it for troubleshooting purposes. Style and approach This step-by-step guide on Wireshark 2 starts with capturing and filtering traffic and follows with analysis and statistics, as well as all the new features of Wireshark 2.

Manage on-premises and cloud IT assets from one console About This Book ? Empower yourself with practical recipes to collect and analyze operational insights on Windows and Linux servers in your on premises datacenters and in any public cloud environments such as Azure and AWS. ? Build capabilities through practical tasks and techniques to collect and analyze machine data ? Address business challenges and discover means to accommodate workloads and instances in a low cost manner Who This Book Is For This book is written for the IT professional and general reader who is interested in technology themes such as DevOps, Big Data Analytics, and digital transformation concepts. Azure and other cloud platform administrators, cloud professionals, and technology analysts who would like to solve everyday problems quickly and efficiently with hybrid management tools available in the Microsoft product ecosystem will derive much value from this book. Prior experience with OMS 2012 would be helpful. What You Will Learn ? Understand the important architectural considerations and strategies for OMS ? Use advanced search query commands and strategies to derive insights from indexed data ? Make use of alerting in OMS such as alert actions, and available options for the entire lifecycle of the alert ? Discover some practical tips for monitoring Azure container service containers and clusters using OMS ? Review and use the backup options available through the Azure backup service, as well as data recovery options available through Azure Site Recovery (ASR) ? Understand how to advance important DevOps concepts within your IT organization ? Learn how to manage configurations and automate process In Detail Microsoft Operations Management Suite Cookbook begins with an overview of how to hit the ground running with OMS insights and analytics. Next, you will learn to search and analyze data to retrieve actionable insights, review alert generation from the analyzed data, and use basic and advanced Log search queries in Azure Log Analytics. Following this, you will explore some other management solutions that provide functionality related to workload assessment, application dependency mapping, automation and configuration management, and security and compliance. You will also become well versed with the data protection and recovery functionalities of OMS Protection and Recovery, and learn how to use Azure Automation components and features in OMS. Finally you will learn how to evaluate key considerations for using the Security and Audit solution, and working with Security and Compliance in OMS. By the end of the book, you will be able to configure and utilize solution offerings in OMS, understand OMS workflows, how to unlock insights, integrate capabilities into new or existing workflows, manage configurations, and automate tasks and processes. Style and approach This is a recipe based guide where early chapters introduce the main concepts and key capabilities, and the later chapters delve into more advance concepts.

Develop and manage applications on the AWS and OpenStack platforms with this comprehensive learning guide. About This Book ? A step-by-step guide to help you develop applications on the hybrid cloud platform. ? Acquire an in-depth understanding of the OpenStack and AWS cloud platforms. ? Extensive source code examples for OpenStack and AWS applications. ? Easily troubleshoot OpenStack and AWS issues. ? Understand the best practices and security measures for the hybrid cloud platform. Who This Book Is For If you are an IT professional, developer, or a DevOps engineer looking to develop and manage your applications on the hybrid cloud platform, then this book is for you. Some prior knowledge of the public and private cloud will enhance your skills. Developers looking to build applications using AWS or OpenStack services will also benefit from this book. What You Will Learn ? Understand the hybrid cloud platform ? Explore the AWS and OpenStack cloud platforms in depth ? Develop AWS applications with source code examples ? Develop OpenStack applications with source code examples ? Troubleshoot OpenStack and AWS ? Learn hybrid cloud best practices ? Understand security measures on the hybrid cloud In Detail This book introduces you to the hybrid cloud platform, and focuses on the AWS public cloud and OpenStack private cloud platforms. It provides a deep dive into the AWS and OpenStack cloud platform services that are essential for developing hybrid cloud applications. You will learn to develop applications on AWS and OpenStack platforms with ease by leveraging various cloud services and taking advantage of PaaS. The book provides you with the ability to leverage the flexibility of choosing a cloud platform for migrating your existing resources to the cloud, as well as developing hybrid cloud applications that can migrate virtual machine instances from AWS to OpenStack and vice versa. You will also be able to build and test cloud applications without worrying about the system that your development environment supports. The book also provides an in-depth understanding of the best practices that are followed across the industry for developing cloud applications, as well as for adapting the hybrid cloud platform. Lastly, it also sheds light on various troubleshooting techniques for OpenStack and AWS cloud platform services that are consumed by hybrid cloud applications. By the end of this book, you will have a deep understanding of the hybrid cloud platform and will be able to develop robust, efficient, modular, scalable, and ?exible cloud applications. Style and approach This book follows a practical approach to become familiar with the AWS and OpenStack platform from a developer's perspective.

Learn to build a high-performance functional prototype of a voting web application from scratch using Elixir and Phoenix About This Book ? Build a strong foundation in Functional-Programming techniques while learning to build compelling web applications ? Understand the Elixir Concurrency and parallelization model to build high-performing blazingly fast applications ? Learn to test, debug and deploy your web applications using Phoenix framework Who This Book Is For This book is for people with a basic knowledge of Elixir, who want to start building web applications. Prior experience with web technologies is assumed. What You Will Learn ? Learn Phoenix Framework fundamentals and v1.3's new application structure ? Build real-time applications with channels and presence ? Utilize GenServers and other OTP fundamentals to keep an application stable ? Track users as they sign in and out of chat with Phoenix’s built-in presence functionality ? Write your own database interaction code that is safe, bug-free, and easy to work with ? Explore testing and debugging methodologies to understand a real software development lifecycle for a Phoenix application ? Deploy and run your Phoenix application in production In Detail Phoenix is a modern web development framework that is used to build API’s and web applications. It is built on Elixir and runs on Erlang VM which makes it much faster than other options. With Elixir and Phoenix, you build your application the right way, ready to scale and ready for the increasing demands of real-time web applications. This book covers the basics of the Phoenix web framework, showing you how to build a community voting application, and is divided into three parts. In the first part, you will be introduced to Phoenix and Elixir and understand the core terminologies that are used to describe them. You will also learn to build controller pages, store and retrieve data, add users to your app pages and protect your database. In the second section you will be able to reinforce your knowledge of architecting real time applications in phoenix and not only debug these applications but also diagnose issues in them. In the third and final section you will have the complete understanding of deploying and running the phoenix application and should be comfortable to make your first application release By the end of this book, you'll have a strong grasp of all of the core fundamentals of the Phoenix framework, and will have built a full production-ready web application from scratch. Style and approach Covers the basics of the Phoenix web framework by building a complete real-time application and showing the new structure changes introduced in Phoenix v1.3

Explore big data concepts, platforms, analytics, and their applications using the power of Hadoop 3 About This Book ? Learn Hadoop 3 to build effective big data analytics solutions on-premise and on cloud ? Integrate Hadoop with other big data tools such as R, Python, Apache Spark, and Apache Flink ? Exploit big data using Hadoop 3 with real-world examples Who This Book Is For Big Data Analytics with Hadoop 3 is for you if you are looking to build high-performance analytics solutions for your enterprise or business using Hadoop 3’s powerful features, or you’re new to big data analytics. A basic understanding of the Java programming language is required. What You Will Learn ? Explore the new features of Hadoop 3 along with HDFS, YARN, and MapReduce ? Get well-versed with the analytical capabilities of Hadoop ecosystem using practical examples ? Integrate Hadoop with R and Python for more efficient big data processing ? Learn to use Hadoop with Apache Spark and Apache Flink for real-time data analytics ? Set up a Hadoop cluster on AWS cloud ? Perform big data analytics on AWS using Elastic Map Reduce In Detail Apache Hadoop is the most popular platform for big data processing, and can be combined with a host of other big data tools to build powerful analytics solutions. Big Data Analytics with Hadoop 3 shows you how to do just that, by providing insights into the software as well as its benefits with the help of practical examples. Once you have taken a tour of Hadoop 3’s latest features, you will get an overview of HDFS, MapReduce, and YARN, and how they enable faster, more efficient big data processing. You will then move on to learning how to integrate Hadoop with the open source tools, such as Python and R, to analyze and visualize data and perform statistical computing on big data. As you get acquainted with all this, you will explore how to use Hadoop 3 with Apache Spark and Apache Flink for real-time data analytics and stream processing. In addition to this, you will understand how to use Hadoop to build analytics solutions on the cloud and an end-to-end pipeline to perform big data analysis using practical use cases. By the end of this book, you will be well-versed with the analytical capabilities of the Hadoop ecosystem. You will be able to build powerful solutions to perform big data analytics and get insight effortlessly. Style and approach Filled with practical examples and use cases, this book will not only help you get up and running with Hadoop, but will also take you farther down the road to deal with Big Data Analytics

Building Complete E-commerce/Shopping Cart Application About This Book ? Follow best practices and explore techniques such as clustering and caching to achieve a reactive, scalable web service ? Leverage the .NET Framework to quickly implement RESTful endpoints. ? Learn to implement a client library for a RESTful web service using ASP.NET Core. Who This Book Is For This book is intended for those who want to learn to build RESTful web services with the latest .NET Core Framework. To make best use of the code samples included in the book, you should have a basic knowledge of C# and .NET Core. What You Will Learn ? Add basic authentication to your RESTful API ? Create a Carts Controller and Orders Controller to manage and process Orders ? Intercept HTTP requests and responses by building your own middleware ? Test service calls using Postman and Advanced REST Client ? Secure your data/application using annotations In Detail REST is an architectural style that tackles the challenges of building scalable web services. In today's connected world, APIs have taken a central role on the web. APIs provide the fabric through which systems interact, and REST has become synonymous with APIs. The depth, breadth, and ease of use of ASP.NET Core makes it a breeze for developers to work with for building robust web APIs. This book takes you through the design of RESTful web services and leverages the ASP.NET Core framework to implement these services. This book begins by introducing you to the basics of the philosophy behind REST. You'll go through the steps of designing and implementing an enterprise-grade RESTful web service. This book takes a practical approach, that you can apply to your own circumstances. This book brings forth the power of the latest .NET Core release, working with MVC. Later, you will learn about the use of the framework to explore approaches to tackle resilience, security, and scalability concerns. You will explore the steps to improve the performance of your applications. You'll also learn techniques to deal with security in web APIs and discover how to implement unit and integration test strategies. By the end of the book, you will have a complete understanding of Building a client for RESTful web services, along with some scaling techniques. Style and approach This book is a step-by-step, hands-on guide to designing and building RESTful web services.

Write modern natural language processing applications using deep learning algorithms and TensorFlow About This Book ? Focuses on more efficient natural language processing using TensorFlow ? Covers NLP as a field in its own right to improve understanding for choosing TensorFlow tools and other deep learning approaches ? Provides choices for how to process and evaluate large unstructured text datasets ? Learn to apply the TensorFlow toolbox to specific tasks in the most interesting field in artificial intelligence Who This Book Is For This book is for Python developers with a strong interest in deep learning, who want to learn how to leverage TensorFlow to simplify NLP tasks. Fundamental Python skills are assumed, as well as some knowledge of machine learning and undergraduate-level calculus and linear algebra. No previous natural language processing experience required, although some background in NLP or computational linguistics will be helpful. What You Will Learn ? Core concepts of NLP and various approaches to natural language processing ? How to solve NLP tasks by applying TensorFlow functions to create neural networks ? Strategies to process large amounts of data into word representations that can be used by deep learning applications ? Techniques for performing sentence classification and language generation using CNNs and RNNs ? About employing state-of-the art advanced RNNs, like long short-term memory, to solve complex text generation tasks ? How to write automatic translation programs and implement an actual neural machine translator from scratch ? The trends and innovations that are paving the future in NLP In Detail Natural language processing (NLP) supplies the majority of data available to deep learning applications, while TensorFlow is the most important deep learning framework currently available. Natural Language Processing with TensorFlow brings TensorFlow and NLP together to give you invaluable tools to work with the immense volume of unstructured data in today’s data streams, and apply these tools to specific NLP tasks. Thushan Ganegedara starts by giving you a grounding in NLP and TensorFlow basics. You'll then learn how to use Word2vec, including advanced extensions, to create word embeddings that turn sequences of words into vectors accessible to deep learning algorithms. Chapters on classical deep learning algorithms, like convolutional neural networks (CNN) and recurrent neural networks (RNN), demonstrate important NLP tasks as sentence classification and language generation. You will learn how to apply high-performance RNN models, like long short-term memory (LSTM) cells, to NLP tasks. You will also explore neural machine translation and implement a neural machine translator. After reading this book, you will gain an understanding of NLP and you'll have the skills to apply TensorFlow in deep learning NLP applications, and how to perform specific NLP tasks. Style and approach The book provides an emphasis on both the theory and practice of natural language processing. It introduces the reader to existing TensorFlow functions and explains how to apply them while writing NLP algorithms. The popular Word2vec method is used to teach the essential process of learning word representations. The book focuses on how to apply classical deep learning to NLP, as well as exploring cutting edge and emerging approaches. Specific examples are used to make the concepts and techniques concrete.

Transform machine data into powerful analytical intelligence using Splunk About This Book ? Analyze and visualize machine data to step into the world of Splunk! ? Leverage the exceptional analysis and visualization capabilities to make informed decisions for your business ? This easy-to-follow, practical book can be used by anyone - even if you have never managed data before Who This Book Is For This book is for the beginners who want to get well versed in the services offered by Splunk 7. If you want to be a data/business analyst or want to be a system administrator, this book is what you want. No prior knowledge of Splunk is required. What You Will Learn ? Install and configure Splunk for personal use ? Store event data in Splunk indexes, classify events into sources, and add data fields ? Learn essential Splunk Search Processing Language commands and best practices ? Create powerful real-time or user-input dashboards ? Be proactive by implementing alerts and scheduled reports ? Tips from the Fez: best practices using Splunk features and add-ons ? Understand security and deployment considerations for taking Splunk to an organizational level In Detail Splunk is a search, reporting, and analytics software platform for machine data, which has an ever-growing market adoption rate. More organizations than ever are adopting Splunk to make informed decisions in areas such as IT operations, information security, and the Internet of Things. The first two chapters of the book will get you started with a simple Splunk installation and set up of a sample machine data generator, called Eventgen. After this, you will learn to create various reports, dashboards, and alerts. You will also explore Splunk's Pivot functionality to model data for business users. You will then have the opportunity to test-drive Splunk's powerful HTTP Event Collector. After covering the core Splunk functionality, you'll be provided with some real-world best practices for using Splunk, and information on how to build upon what you've learned in this book. Throughout the book, there will be additional comments and best practice recommendations from a member of the SplunkTrust Community, called "Tips from the Fez". Style and approach This fast-paced, example-rich guide will help you analyze and visualize machine data with Splunk through simple, practical instructions and recommendations.

Explore the high-in demand core DevOps strategies with powerful DevOps tools such as Ansible, Jenkins, and Chef About This Book ? Get acquainted with methodologies and tools of the DevOps framework ? Perform continuous integration, delivery, deployment, and monitoring using DevOps tools ? Explore popular tools such as Git, Jenkins, Maven, Gerrit, Nexus, Selenium, and so on ? Embedded with assessments that will help you revise the concepts you have learned in this book Who This Book Is For This book is for engineers, architects, and developers, who wish to learn the core strategies of DevOps. What You Will Learn ? Get familiar with life cycle models, maturity states, progression and best practices of DevOps frameworks ? Learn to set up Jenkins and integrate it with Git ? Know how to build jobs and perform testing with Jenkins ? Implement infrastructure automation (Infrastructure as Code) with tools such as Chef and Ansible ? Understand continuous monitoring process with tools such as Splunk and Nagios ? Learn how Splunk improves the code quality In Detail DevOps is the most widely used software engineering culture and practice that aim sat software development and operation. Continuous integration is a cornerstone technique of DevOps that merges software code updates from developers into a shared central mainline. This book takes a practical approach and covers the tools and strategies of DevOps. It starts with familiarizing you with DevOps framework and then shows how toper form continuous delivery, integration, and deployment with DevOps. You will explore DevOps process maturity frameworks and progression models with checklist templates for each phase of DevOps. You will also be familiar with agile terminology, methodology, and the benefits accrued by an organization by adopting it. You will also get acquainted with popular tools such as Git, Jenkins ,Maven, Gerrit, Nexus, Selenium, and so on.You will learn configuration, automation, and the implementation of infrastructure automation (Infrastructure as Code) with tools such as Chef and Ansible. This book is ideal for engineers, architects, and developers, who wish to learn the core strategies of DevOps. Style and approach This book takes a practical approach and covers the tools and strategies of DevOps. It starts with familiarizing you with DevOps framework and then shows how to perform continuous delivery, integration, and deployment with DevOps. Note: This book is a blend of text and quizzes, all packaged up keeping your journey in mind. It includes content from the following Packt product: ? Hands-on DevOps by Sricharan Vadapalli

Takes you through creating your own API, building a full real-time web app, securing your Node systems, and practical applications of the latest Async and Await technologies. It maps out everything in a comprehensive, easy-to-follow package designed to get you up and running quickly. About This Book ? Entirely project-based and practical ? Explains the "why" of Node.js features, not just the "how", providing with a deep understanding and enabling you to easily apply concepts in your own applications ? Covers the full range of technologies around Node.js – npm, MongoDB, version control with Git, and many more Who This Book Is For This book is for anyone looking to launch their own Node applications, switch careers, or freelance as a Node developer. You should have a basic understanding of JavaScript in order to follow this book. This book follows directly on from Learning Node.js Development, but more advanced readers can benefit from this book without having read the first part. What You Will Learn ? Develop, test, and deploy real-world Node.js applications ? Master Node.js by building practical, working examples ? Use awesome third-party Node modules such as MongoDB, Mongoose, Socket.io, and Express ? Create real-time web applications ? Explore async and await in ES7 In Detail Advanced Node.js Development is a practical, project-based book that provides you with all you need to progress as a Node.js developer. Node is a ubiquitous technology on the modern web, and an essential part of any web developer’s toolkit. If you're looking to create real-world Node applications, or you want to switch careers or launch a side-project to generate some extra income, then you're in the right place. This book was written around a single goal: turning you into a professional Node developer capable of developing, testing, and deploying real-world production applications. There's no better time to dive in. According to the 2018 Stack Overflow Survey, Node is in the top ten for back-end popularity and back-end salary. This book is built from the ground up around the latest version of Node.js (version 9.x.x). You'll be learning all the cutting-edge features available only in the latest software versions. This book delivers advanced skills that you need to become a professional Node developer. Along this journey you'll create your own API, you'll build a full real-time web app and create projects that apply the latest Async and Await technologies. Andrew Mead maps everything out for you in this book so that you can learn how to build powerful Node.js projects in a comprehensive, easy-to-follow package designed to get you up and running quickly. Style and approach This book is entirely project-based. From the very beginning, you'll be programming every single app and completing various challenges designed to help test and reinforce what you've learned. There's no copying-and-pasting here. This book is about writing code and building projects.

Create and manage a clear working IT asset management strategy with this unique guide About This Book ? A detailed IT Asset Management (ITAM) guidebook with real-world templates that can be converted into working ITAM documents. ? Includes in-depth discussion on how risk management has changed and the possible solutions needed to address the new normal ? A step-by-step ITAM manual for newbies as well as seasoned ITAM veterans Who This Book Is For This book is intended for CIOs, VPs and CTOs of mid to large-sized enterprises and organizations. If you are dealing with changes such as mergers, acquisitions, divestitures, new products or services, cyber security, mandated regulations, expansion, and much more, this book will help you too. What You Will Learn ? Close the hidden risk gaps created by IT assets (hardware and software) ? Create and manage a clear working proactive ITAM and SAM program and policy ? A clear, concise explanation of what IT Asset Management is, the benefits, and results ? A clear, concise explanation of what Software Asset Management is, the benefits, and results ? The best ways to manage a software audit and how to be prepared for one ? Considerations for selecting the best technology for a specific company including what questions should be asked at the onset. ? Increasing ITAM program and project success with change management In Detail IT Asset Management (ITAM) supports life cycle management and strategic decision making for an IT environment. This book is a detailed IT Asset Management (ITAM) guidebook with real-world templates that can be converted into working ITAM documents. It is a step-by-step IT asset management manual for the newbies as well as the seasoned ITAM veterans, providing a unique insight into asset management. It discusses how risk management has changed over time and the possible solutions needed to address the new normal. The book also includes considerations for selecting the best technology for a specific company including what questions should be asked at the onset, as well as the best ways to manage a software audit and how to be prepared for one. This book is your perfect guide to create holistic IT asset management and Software asset management programs that close the risk gaps, increases productivity and results in cost efficiencies. It allows the IT Asset Managers, Software Asset Managers, and/or the full IT Asset Management (ITAM) ITAM/SAM program team to take a deep dive by using the templates offered in the guidebook. You will be aware of the specific roles and responsibilities for every aspect of IT asset management, software asset management, and software license compliance audit response. By the end of this book, you will be well aware of what IT and Software Asset Management is all about and the different steps, processes, and roles required to truly master it. By the end of this book, you will be well aware of what IT Asset Management is all about and the different skills required to truly master it. Style and approach Packed with important discussion points, examples, case studies, templates, and checklists.

Harness the power of React Native to build 4 real-world apps About This Book ? Build quirky and fun projects from scratch and become efficient with React Native ? Learn to build professional Android and iOS applications using your existing JavaScript knowledge ? Use isomorphic principles to build mobile apps that offer a native user experience ? Embedded with assessments that will help you revise the concepts you have learned in this course Who This Book Is For This book is for developers who want to build amazing cross-platform apps with React Native. What You Will Learn ? Structure React Native projects to ease maintenance and extensibility ? Optimize a project to speed up development ? Use external modules to speed up the development and maintenance of your projects ? Explore the different UI and code patterns to be used for iOS and Android ? Get to know the best practices when building apps in React Native In Detail React Native helps web and mobile developers to build cross-platform apps that perform at the same level as any other natively developed app. The range of apps that can be built using this library is huge. From e-commerce to games, React Native is a good fit for any mobile project due to its flexibility and extendable nature. This project-based book consists of four standalone projects. Each project will help you gain a sound understanding of the framework and build mobile apps with native user experience. Starting with a simple standalone car booking app, you will progressively move on to building advanced apps by adding connectivity with external APIs, using native features, such as the camera or microphone, in the mobile device, integrating with state management libraries such as Redux or MobX, or leveraging React Native’s performance by building a full-featured game. This book is ideal for developers who want to build amazing cross-platform apps with React Native. This book is embedded with useful assessments that will help you revise the concepts you have learned in this book. Style and approach This project-based book consists of four projects. Each project is a standalone project that covers the core techniques and concepts of React Native. Note: This book is a blend of text and quizzes, all packaged up keeping your journey in mind. It includes content from the following Packt products: ? React Native Blueprints by Emilio Rodriguez Martinez

Text processing and pattern matching simplified About This Book ? Master the fastest and most elegant big data munging language ? Implement text processing and pattern matching using the advanced features of AWK and GAWK ? Implement debugging and inter-process communication using GAWK Who This Book Is For This book is for developers or analysts who are inclined to learn how to do text processing and data extraction in a Unix-like environment. Basic understanding of Linux operating system and shell scripting will help you to get the most out of the book. What You Will Learn ? Create and use different expressions and control flow statements in AWK ? Use Regular Expressions with AWK for effective text-processing ? Use built-in and user-defined variables to write AWK programs ? Use redirections in AWK programs and create structured reports ? Handle non-decimal input, 2-way inter-process communication with Gawk ? Create small scripts to reformat data to match patterns and process texts In Detail AWK is one of the most primitive and powerful utilities which exists in all Unix and Unix-like distributions. It is used as a command-line utility when performing a basic text-processing operation, and as programming language when dealing with complex text-processing and mining tasks. With this book, you will have the required expertise to practice advanced AWK programming in real-life examples. The book starts off with an introduction to AWK essentials. You will then be introduced to regular expressions, AWK variables and constants, arrays and AWK functions and more. The book then delves deeper into more complex tasks, such as printing formatted output in AWK, control flow statements, GNU's implementation of AWK covering the advanced features of GNU AWK, such as network communication, debugging, and inter-process communication in the GAWK programming language which is not easily possible with AWK. By the end of this book, the reader will have worked on the practical implementation of text processing and pattern matching using AWK to perform routine tasks. Style and approach An easy-to-follow, step by step guide which will help you get to grips with real-world applications of AWK programming.

Leverage the power of Tensorflow to design deep learning systems for a variety of real-world scenarios About This Book ? Build efficient deep learning pipelines using the popular Tensorflow framework ? Train neural networks such as ConvNets, generative models, and LSTMs ? Includes projects related to Computer Vision, stock prediction, chatbots and more Who This Book Is For This book is for data scientists, machine learning developers as well as deep learning practitioners, who want to build interesting deep learning projects that leverage the power of Tensorflow. Some understanding of machine learning and deep learning, and familiarity with the TensorFlow framework is all you need to get started with this book. What You Will Learn ? Set up the TensorFlow environment for deep learning ? Construct your own ConvNets for effective image processing ? Use LSTMs for image caption generation ? Forecast stock prediction accurately with an LSTM architecture ? Learn what semantic matching is by detecting duplicate Quora questions ? Set up an AWS instance with TensorFlow to train GANs ? Train and set up a chatbot to understand and interpret human input ? Build an AI capable of playing a video game by itself –and win it! In Detail TensorFlow is one of the most popular frameworks used for machine learning and, more recently, deep learning. It provides a fast and efficient framework for training different kinds of deep learning models, with very high accuracy. This book is your guide to master deep learning with TensorFlow with the help of 10 real-world projects. TensorFlow Deep Learning Projects starts with setting up the right TensorFlow environment for deep learning. Learn to train different types of deep learning models using TensorFlow, including Convolutional Neural Networks, Recurrent Neural Networks, LSTMs, and Generative Adversarial Networks. While doing so, you will build end-to-end deep learning solutions to tackle different real-world problems in image processing, recommendation systems, stock prediction, and building chatbots, to name a few. You will also develop systems that perform machine translation, and use reinforcement learning techniques to play games. By the end of this book, you will have mastered all the concepts of deep learning and their implementation with TensorFlow, and will be able to build and train your own deep learning models with TensorFlow confidently. Style and approach This book contains 10 unique, end-to-end projects covering all aspects of deep learning and their implementations with TensorFlow. Each project will equip you with a unique skillset in training efficient deep learning models, and empower you to implement your own projects more confidently

Create next-generation Augmented Reality and Mixed Reality apps with the latest version of Google ARCore About This Book ? Harness the power of the Google’s new augmented reality (AR) platform ARCore to build cutting-edge Augmented reality apps ? Learn core concepts of Environmental Understanding, Immersive Computing, and Motion Tracking with ARCore ? Extend your application by combining ARCore with OpenGL, Machine Learning and more. Who This Book Is For This book is for web and mobile developers who have broad programming knowledge on Java or JavaScript or C# and want to develop Augmented Reality applications with Google ArCore. To follow this book no prior experience with AR development, 3D, or 3D math experience is needed. What You Will Learn ? Build and deploy your Augmented Reality app to the Android, Web, and Unity platforms ? Implement ARCore to identify and visualize objects as point clouds, planes, surfaces, and/or meshes ? Explore advanced concepts of environmental understanding using Google ARCore and OpenGL ES with Java ? Create light levels from ARCore and create a C# script to watch and propagate lighting changes in a scene ? Develop graphics shaders that react to changes in lighting and map the environment to place objects in Unity/C# ? Integrate motion tracking with the Web ARCore API and Google Street View to create a combined AR/VR experience In Detail Are you a mobile developer or web developer who wants to create immersive and cool Augmented Reality apps with the latest Google ARCore platform? If so, this book will help you jump right into developing with ARCore and will help you create a step by step AR app easily. This book will teach you how to implement the core features of ARCore starting from the fundamentals of 3D rendering to more advanced concepts such as lighting, shaders, Machine Learning, and others. We’ll begin with the basics of building a project on three platforms: web, Android, and Unity. Next, we’ll go through the ARCore concepts of motion tracking, environmental understanding, and light estimation. For each core concept, you’ll work on a practical project to use and extend the ARCore feature, from learning the basics of 3D rendering and lighting to exploring more advanced concepts. You’ll write custom shaders to light virtual objects in AR, then build a neural network to recognize the environment and explore even grander applications by using ARCore in mixed reality. At the end of the book, you’ll see how to implement motion tracking and environment learning, create animations and sounds, generate virtual characters, and simulate them on your screen. Style and approach Practical examples that will take you through the basics of ARcore and teach you how to build an app using it.

Learn, by example, the fundamentals of data analysis as well as several intermediate to advanced methods and techniques ranging from classification and regression to Bayesian methods and MCMC, which can be put to immediate use. About This Book ? Analyze your data using R – the most powerful statistical programming language ? Learn how to implement applied statistics using practical use-cases ? Use popular R packages to work with unstructured and structured data Who This Book Is For Budding data scientists and data analysts who are new to the concept of data analysis, or who want to build efficient analytical models in R will find this book to be useful. No prior exposure to data analysis is needed, although a fundamental understanding of the R programming language is required to get the best out of this book. What You Will Learn ? Gain a thorough understanding of statistical reasoning and sampling theory ? Employ hypothesis testing to draw inferences from your data ? Learn Bayesian methods for estimating parameters ? Train regression, classification, and time series models ? Handle missing data gracefully using multiple imputation ? Identify and manage problematic data points ? Learn how to scale your analyses to larger data with Rcpp, data.table, dplyr, and parallelization ? Put best practices into effect to make your job easier and facilitate reproducibility In Detail Frequently the tool of choice for academics, R has spread deep into the private sector and can be found in the production pipelines at some of the most advanced and successful enterprises. The power and domain-specificity of R allows the user to express complex analytics easily, quickly, and succinctly. Starting with the basics of R and statistical reasoning, this book dives into advanced predictive analytics, showing how to apply those techniques to real-world data though with real-world examples. Packed with engaging problems and exercises, this book begins with a review of R and its syntax with packages like Rcpp, ggplot2, and dplyr. From there, get to grips with the fundamentals of applied statistics and build on this knowledge to perform sophisticated and powerful analytics. Solve the difficulties relating to performing data analysis in practice and find solutions to working with messy data, large data, communicating results, and facilitating reproducibility. This book is engineered to be an invaluable resource through many stages of anyone’s career as a data analyst. Style and approach An easy-to-follow step by step guide which will help you get to grips with real world application of Data Analysis with R

Learn how to solve real life problems using different methods like logic regression, random forests and SVM’s with TensorFlow. About This Book ? Understand predictive analytics along with its challenges and best practices ? Embedded with assessments that will help you revise the concepts you have learned in this book Who This Book Is For This book is aimed at developers, data analysts, machine learning practitioners, and deep learning enthusiasts who want to build powerful, robust, and accurate predictive models with the power of TensorFlow. What You Will Learn ? Learn TensorFlow features in a real-life problem, followed by detailed TensorFlow installation and configuration ? Explore computation graphs, data, and programming models also get an insight into an example of implementing linear regression model for predictive analytics ? Solve the Titanic survival problem using logistic regression, random forests, and SVMs for predictive analytics ? Dig deeper into predictive analytics and find out how to take advantage of it to cluster records belonging to the certain group or class for a dataset of unsupervised observations ? Learn several examples of how to apply reinforcement learning algorithms for developing predictive models on real-life datasets In Detail Predictive analytics discovers hidden patterns from structured and unstructured data for automated decision making in business intelligence. Predictive decisions are becoming a huge trend worldwide, catering to wide industry sectors by predicting which decisions are more likely to give maximum results. TensorFlow, Google’s brainchild, is immensely popular and extensively used for predictive analysis. This book is a quick learning guide on all the three types of machine learning, that is, supervised, unsupervised, and reinforcement learning with TensorFlow. This book will teach you predictive analytics for high-dimensional and sequence data. In particular, you will learn the linear regression model for regression analysis. You will also learn how to use regression for predicting continuous values. You will learn supervised learning algorithms for predictive analytics. You will explore unsupervised learning and clustering using K-meansYou will then learn how to predict neighborhoods using K-means, and then, see another example of clustering audio clips based on their audio features. This book is ideal for developers, data analysts, machine learning practitioners, and deep learning enthusiasts who want to build powerful, robust, and accurate predictive models with the power of TensorFlow. This book is embedded with useful assessments that will help you revise the concepts you have learned in this book. Style and approach This is a fast-paced guide that provides a quick learning solution to all the three types of machine learning, that is, supervised, unsupervised, and reinforcement learning with TensorFlow Note: This book is a blend of text and quizzes, all packaged up keeping your journey in mind. It includes content from the following Packt product: ? Predictive Analytics with TensorFlow by Md. Rezaul Karim

Leverage the power of Matplotlib to visualize and understand your data more effectively About This Book ? Perform effective data visualization with Matplotlib and get actionable insights from your data ? Design attractive graphs, charts, and 2D plots, and deploy them to the web ? Get the most out of Matplotlib in this practical guide with updated code and examples Who This Book Is For This book is essentially for anyone who wants to create intuitive data visualizations using the Matplotlib library. If you’re a data scientist or analyst and wish to create attractive visualizations using Python, you’ll find this book useful. Some knowledge of Python programming is all you need to get started. What You Will Learn ? Create 2D and 3D static plots such as bar charts, heat maps, and scatter plots ? Get acquainted with GTK+3, Qt5, and wxWidgets to understand the UI backend of Matplotlib ? Develop advanced static plots with third-party packages such as Pandas, GeoPandas, and Seaborn ? Create interactive plots with real-time updates ? Develop web-based, Matplotlib-powered graph visualizations with third-party packages such as Django ? Write data visualization code that is readily expandable on the cloud platform In Detail Python is a general-purpose programming language increasingly being used for data analysis and visualization. Matplotlib is a popular data visualization package in Python used to design effective plots and graphs. This is a practical, hands-on resource to help you visualize data with Python using the Matplotlib library. Matplotlib for Python Developers, Second Edition shows you how to create attractive graphs, charts, and plots using Matplotlib. You will also get a quick introduction to third-party packages, Seaborn, Pandas, Basemap, and Geopandas, and learn how to use them with Matplotlib. After that, you’ll embed and customize your plots in third-party tools such as GTK+3, Qt 5, and wxWidgets. You’ll also be able to tweak the look and feel of your visualization with the help of practical examples provided in this book. Further on, you’ll explore Matplotlib 2.1.x on the web, from a cloud-based platform using third-party packages such as Django. Finally, you will integrate interactive, real-time visualization techniques into your current workflow with the help of practical real-world examples. By the end of this book, you’ll be thoroughly comfortable with using the popular Python data visualization library Matplotlib 2.1.x and leveraging its power to build attractive, insightful, and powerful visualizations. Style and approach Step by step approach to learning the best of Matplotlib 2.1.x

Automate data and model pipelines for faster machine learning applications About This Book ? Build automated modules for different machine learning components ? Understand each component of a machine learning pipeline in depth ? Learn to use different open source AutoML and feature engineering platforms Who This Book Is For If you’re a budding data scientist, data analyst, or Machine Learning enthusiast and are new to the concept of automated machine learning, this book is ideal for you. You’ll also find this book useful if you’re an ML engineer or data professional interested in developing quick machine learning pipelines for your projects. Prior exposure to Python programming will help you get the best out of this book. What You Will Learn ? Understand the fundamentals of Automated Machine Learning systems ? Explore auto-sklearn and MLBox for AutoML tasks ? Automate your preprocessing methods along with feature transformation ? Enhance feature selection and generation using the Python stack ? Assemble individual components of ML into a complete AutoML framework ? Demystify hyperparameter tuning to optimize your ML models ? Dive into Machine Learning concepts such as neural networks and autoencoders ? Understand the information costs and trade-offs associated with AutoML In Detail AutoML is designed to automate parts of Machine Learning. Readily available AutoML tools are making data science practitioners’ work easy and are received well in the advanced analytics community. Automated Machine Learning covers the necessary foundation needed to create automated machine learning modules and helps you get up to speed with them in the most practical way possible. In this book, you’ll learn how to automate different tasks in the machine learning pipeline such as data preprocessing, feature selection, model training, model optimization, and much more. In addition to this, it demonstrates how you can use the available automation libraries, such as auto-sklearn and MLBox, and create and extend your own custom AutoML components for Machine Learning. By the end of this book, you will have a clearer understanding of the different aspects of automated Machine Learning, and you’ll be able to incorporate automation tasks using practical datasets. You can leverage your learning from this book to implement Machine Learning in your projects and get a step closer to winning various machine learning competitions. Style and approach Step by step approach to understand how to automate your machine learning tasks

A step by step guide for beginners to create interactive and dynamic websites from scratch. About This Book ? A fun-filled book with incrementing projects that would help you learn and adapt the fundamentals of web development ? Bring your web design to life with the help of HTML, CSS, JQuery, and learn to kick-start your future projects with Bootstrap ? Explore popular web development techniques such as responsive, adaptive, and material design and initiate yourself with Vue.js Who This Book Is For This book is for anyone who wants to learn about web development regardless of previous experience. It's perfect for complete beginners with zero experience; it's also great for anyone who does have some experience in a few technologies (such as HTML and CSS) but not all of them. What You Will Learn ? Understand the importance of web design and the basic design components ? Learn HTML5 and CSS3 ? Difference between adaptive and responsive web design ? Learn how to create your first website ? Add interaction and dynamic content to your website with JavaScript and JQuery ? Implement Bootstrap Framework in your project ? Get familiar with server-side rendering In Detail Web design is the process of creating websites. It encompasses several different aspects, including webpage layout, content production, and graphic design. This book offers you everything you need to know to build your websites. The book starts off by explaining the importance of web design and the basic design components used in website development. It'll show you insider tips to work quickly and efficiently with web technologies such as HTML5, CSS3, and JavaScript, concluding with a project on creating a static site with good layout. Once you've got that locked down, we'll get our hands dirty by diving straight into learning JavaScript and JQuery, ending with a project on creating dynamic content for your website. After getting our basic website up and running with the dynamic functionalities you'll move on to building your own responsive websites using more advanced techniques such as Bootstrap. Later you will learn smart ways to add dynamic content, and modern UI techniques such as Adaptive UI and Material Design. This will help you understand important concepts such as server-side rendering and UI components. Finally we take a look at various developer tools to ease your web development process. Style and approach This is a fun-filled book with conversational and engaging content ; with each incrementing project, you'll would easily learn and adapt the fundamentals of web development. Each project showcases a different use case and incrementally teaches the web development basics.

Leverage the power of the popular Jupyter notebooks to simplify your data science tasks without any hassle About This Book ? Create and share interactive documents with live code, text and visualizations ? Integrate popular programming languages such as Python, R, Julia, Scala with Jupyter ? Develop your widgets and interactive dashboards with these innovative recipes Who This Book Is For This cookbook is for data science professionals, developers, technical data analysts, and programmers who want to execute technical coding, visualize output, and do scientific computing in one tool. Prior understanding of data science concepts will be helpful, but not mandatory, to use this book. What You Will Learn ? Install Jupyter and configure engines for Python, R, Scala and more ? Access and retrieve data on Jupyter Notebooks ? Create interactive visualizations and dashboards for different scenarios ? Convert and share your dynamic codes using HTML, JavaScript, Docker, and more ? Create custom user data interactions using various Jupyter widgets ? Manage user authentication and file permissions ? Interact with Big Data to perform numerical computing and statistical modeling ? Get familiar with Jupyter's next-gen user interface - JupyterLab In Detail Jupyter has garnered a strong interest in the data science community of late, as it makes common data processing and analysis tasks much simpler. This book is for data science professionals who want to master various tasks related to Jupyter to create efficient, easy-to-share, scientific applications. The book starts with recipes on installing and running the Jupyter Notebook system on various platforms and configuring the various packages that can be used with it. You will then see how you can implement different programming languages and frameworks, such as Python, R, Julia, JavaScript, Scala, and Spark on your Jupyter Notebook. This book contains intuitive recipes on building interactive widgets to manipulate and visualize data in real time, sharing your code, creating a multi-user environment, and organizing your notebook. You will then get hands-on experience with Jupyter Labs, microservices, and deploying them on the web. By the end of this book, you will have taken your knowledge of Jupyter to the next level to perform all key tasks associated with it. Style and approach The recipes in this book are highly practical and very easy to follow, and include tips and tricks that will help you crack any problem that you might come across while getting the most out of your Jupyter notebook.