Get up and running with the fundamentals of Amazon Alexa and build exciting IoT projects About This Book ? Gain hands-on experience of working with Amazon Echo and Alexa ? Build exciting IoT projects using Amazon Echo ? Learn about voice-enabled smart devices Who This Book Is For Alexa Skills Projects is for individuals who want to have a deep understanding of the underlying technology that drives Amazon Echo and Alexa, and how it can be integrated with the Internet of Things to develop hands-on projects. What You Will Learn ? Understand how Amazon Echo is already being used in various domains ? Discover how an Alexa Skill is architected ? Get a clear understanding of how some of the most popular Alexa Skills work ? Design Alexa Skills for specific purposes and interact with Amazon Echo to execute them ? Gain experience of programming for Amazon Echo ? Explore future applications of Amazon Echo and other voice-activated devices In Detail Amazon Echo is a smart speaker developed by Amazon, which connects to Amazon’s Alexa Voice Service and is entirely controlled by voice commands. Amazon Echo is currently being used for a variety of purposes such as home automation, asking generic queries, and even ordering a cab or pizza. Alexa Skills Projects starts with a basic introduction to Amazon Alexa and Echo. You will then deep dive into Alexa Programming concepts such as Intents, Slots, Lambdas and maintaining your skill’s state using DynamoDB. You will get a clear understanding of how some of the most popular Alexa Skills work, and gain experience of working with real-world Amazon Echo applications. In the concluding chapters, you will explore the future of voice-enabled applications and their coverage with respect to the Internet of Things. By the end of the book, you will have learned to design Alexa Skills for specific purposes and interact with Amazon Echo to execute these skills. Style and approach A practical guide filled with real world examples that will help you understand the process of creating Alexa Skills from scratch and it's real world applications.

A perfect guide to speed up the predicting power of machine learning algorithms About This Book ? Design, discover, and create dynamic, efficient features for your machine learning application ? Understand your data in-depth and derive astonishing data insights with the help of this Guide ? Grasp powerful feature-engineering techniques and build machine learning systems Who This Book Is For If you are a data science professional or a machine learning engineer looking to strengthen your predictive analytics model, then this book is a perfect guide for you. Some basic understanding of the machine learning concepts and Python *ing would be enough to get started with this book. What You Will Learn ? Identify and leverage different feature types ? Clean features in data to improve predictive power ? Understand why and how to perform feature selection, and model error analysis ? Leverage domain knowledge to construct new features ? Deliver features based on mathematical insights ? Use machine-learning algorithms to construct features ? Master feature engineering and optimization ? Harness feature engineering for real world applications through a structured case study In Detail Feature engineering is the most important step in creating powerful machine learning systems. This book will take you through the entire feature-engineering journey to make your machine learning much more systematic and effective. You will start with understanding your data—often the success of your ML models depends on how you leverage different feature types, such as continuous, categorical, and more, You will learn when to include a feature, when to omit it, and why, all by understanding error analysis and the acceptability of your models. You will learn to convert a problem statement into useful new features. You will learn to deliver features driven by business needs as well as mathematical insights. You'll also learn how to use machine learning on your machines, automatically learning amazing features for your data. By the end of the book, you will become proficient in Feature Selection, Feature Learning, and Feature Optimization. Style and approach This step-by-step guide with use cases, examples, and illustrations will help you master the concepts of feature engineering. Along with explaining the fundamentals, the book will also introduce you to slightly advanced concepts later on and will help you implement these techniques in the real world.

Untangle your web scraping complexities and access web data with ease using Python *s About This Book ? Hands-on recipes for advancing your web scraping skills to expert level. ? One-Stop Solution Guide to address complex and challenging web scraping tasks using Python. ? Understand the web page structure and collect meaningful data from the website with ease Who This Book Is For This book is ideal for Python programmers, web administrators, security professionals or someone who wants to perform web analytics would find this book relevant and useful. Familiarity with Python and basic understanding of web scraping would be useful to take full advantage of this book. What You Will Learn ? Use a wide variety of tools to scrape any website and data—including BeautifulSoup, Scrapy, Selenium, and many more ? Master expression languages such as XPath, CSS, and regular expressions to extract web data ? Deal with scraping traps such as hidden form fields, throttling, pagination, and different status codes ? Build robust scraping pipelines with SQS and RabbitMQ ? Scrape assets such as images media and know what to do when Scraper fails to run ? Explore ETL techniques of build a customized crawler, parser, and convert structured and unstructured data from websites ? Deploy and run your scraper-as-aservice in AWS Elastic Container Service In Detail Python Web Scraping Cookbook is a solution-focused book that will teach you techniques to develop high-performance scrapers and deal with crawlers, sitemaps, forms automation, Ajax-based sites, caches, and more.You'll explore a number of real-world scenarios where every part of the development/product life cycle will be fully covered. You will not only develop the skills to design and develop reliable, performance data flows, but also deploy your codebase to an AWS. If you are involved in software engineering, product development, or data mining (or are interested in building data-driven products), you will find this book useful as each recipe has a clear purpose and objective. Right from extracting data from the websites to writing a sophisticated web crawler, the book's independent recipes will be a godsend on the job. This book covers Python libraries, requests, and BeautifulSoup. You will learn about crawling, web spidering, working with AJAX websites, paginated items, and more. You will also learn to tackle problems such as 403 errors, working with proxy, scraping images, LXML, and more. By the end of this book, you will be able to scrape websites more efficiently and to be able to deploy and operate your scraper in the cloud. Style and approach This book is a rich collection of recipes that will come in handy when you are scraping a website using Python. Addressing your common and not-so-common pain points while scraping website, this is a book that you must have on the shelf.

Your one step guide to learn all about AWS networking. About This Book ? Master your networking skills on Public Cloud. ? Gain hands-on experience of using Amazon VPC, Elastic Load Balancing, Direct Connect and other AWS products. ? Implement troubleshooting skills and best practices for security on AWS network. Who This Book Is For This book is targeted towards cloud architects, cloud solution providers, or any stakeholders dealing with networking on AWS Cloud. A prior idea of Amazon Web Services will be an added advantage. What You Will Learn ? Overview of all networking services available in AWS. ? Gain Work with load balance application across different regions. ? Learn auto scale instance based on the increase and decrease of the traffic. ? Deploy application in highly available and fault tolerant manner. ? Configure Route 53 for a web application. ? Troubleshooting tips and best practices at the end In Detail Amazon Web Services (AWS) dominates the public cloud market by a huge margin and it continues to be the first choice for many organizations. Networking has been an area of focus for all the leading cloud service providers. AWS has a suite of network-related products that help to perform network-related task in AWS. This book initially covers the basics of networking in AWS. Then we use AWS VPC to create an isolated virtual cloud for performing network-related tasks. We then provide an overview of AWS Direct Connect after taking a deep dive into scalability and load balancing using Auto scaling feature, Elastic Load Balancing, and Amazon Route S3. Toward the end of the book, we cover some troubleshooting tips and security best practices for your network. By the end of this book, you will have hands-on experience of working with network tasks on AWS. Style and approach A step by step practical guide that helps you use all networking services available in AWS effectively.

Develop and run efficient R *s and predictive models for SQL Server 2017 About This Book ? Learn how you can combine the power of R and SQL Server 2017 to build efficient, cost-effective data science solutions ? Leverage the capabilities of R Services to perform advanced analytics—from data exploration to predictive modeling ? A quick primer with practical examples to help you get up- and- running with SQL Server 2017 Machine Learning Services with R, as part of database solutions with continuous integration / continuous delivery. Who This Book Is For This book is for data analysts, data scientists, and database administrators with some or no experience in R but who are eager to easily deliver practical data science solutions in their day-to-day work (or future projects) using SQL Server. What You Will Learn ? Get an overview of SQL Server 2017 Machine Learning Services with R ? Manage SQL Server Machine Learning Services from installation to configuration and maintenance ? Handle and operationalize R code ? Explore RevoScaleR R algorithms and create predictive models ? Deploy, manage, and monitor database solutions with R ? Extend R with SQL Server 2017 features ? Explore the power of R for database administrators In Detail R Services was one of the most anticipated features in SQL Server 2016, improved significantly and rebranded as SQL Server 2017 Machine Learning Services. Prior to SQL Server 2016, many developers and data scientists were already using R to connect to SQL Server in siloed environments that left a lot to be desired, in order to do additional data analysis, superseding SSAS Data Mining or additional CLR programming functions. With R integrated within SQL Server 2017, these developers and data scientists can now benefit from its integrated, effective, efficient, and more streamlined analytics environment. This book gives you foundational knowledge and insights to help you understand SQL Server 2017 Machine Learning Services with R. First and foremost, the book provides practical examples on how to implement, use, and understand SQL Server and R integration in corporate environments, and also provides explanations and underlying motivations. It covers installing Machine Learning Services;maintaining, deploying, and managing code;and monitoring your services. Delving more deeply into predictive modeling and the RevoScaleR package, this book also provides insights into operationalizing code and exploring and visualizing data. To complete the journey, this book covers the new features in SQL Server 2017 and how they are compatible with R, amplifying their combined power. Style and approach This fast-paced guide will help data scientists and DBAs implement all new data science projects using SQL Server 2017 Machine Learning Services.

Get up and running with all the new features of ECMAScript and explore new ways of coding with JavaScript. About This Book ? Grasp the latest features of ECMAScript and the best way to use it in production code ? Learn newly added native APIs to JS Engine and perform tasks efficiently with a cleaner code base ? Understand the more complex sides of JavaScript such as the inheritance model, low-level memory management, multithreaded environments, and web workers Who This Book Is For This book is for web developers who have some basic programming knowledge and want to learn to write cleaner code with the power of ECMAScript. What You Will Learn ? Implement methods associated with objects as per the latest ECMAScript specification ? Make use of the latest features of ECMAScript ? Make use of many new APIs in HTML5 and modern JavaScript implementation ? Use SharedArrayBuffers for superfast concurrent and parallel programming ? Perform asynchronous programming with JavaScript ? Implement the best ways and practices to perform modular programming in JavaScript In Detail Learn ECMAScript explores implementation of the latest ECMAScript features to add to your developer toolbox, helping you to progress to an advanced level. Learn to add 1 to a variable andsafely access shared memory data within multiple threads to avoid race conditions. You’ll start the book by building on your existing knowledge of JavaScript, covering performing arithmetic operations, using arrow functions and dealing with closures. Next, you will grasp the most commonly used ECMAScript skills such as reflection, proxies, and classes. Furthermore, you’ll learn modularizing the JS code base, implementing JS on the web and how the modern HTML5 + JS APIs provide power to developers on the web. Finally, you will learn the deeper parts of the language, which include making JavaScript multithreaded with dedicated and shared web workers, memory management, shared memory, and atomics. It doesn’t end here; this book is 100% compatible with ES.Next. By the end of this book, you'll have fully mastered all the features of ECMAScript! Style and approach The level goes gradually from basic to advanced so that the reader can adapt at every point and level up their skills at the same time. The chapters are carefully arranged in a manner that makes every concept easy to learn and deploy right away in your code.

Understand the ServiceNow *ing and build an efficient customized ServiceNow instance About This Book ? Customize your ServiceNow instance according to your organization’s needs ? Learn to work with inbuilt JavaScript APIs in ServiceNow ? Take your ServiceNow experience to the next level by learning to * Who This Book Is For This book is targeted toward ServiceNow administrators or anyone willing to learn inbuilt JavaScript APIs used to * and customize ServiceNow instances. Prior experience with ServiceNow is required. What You Will Learn ? Customize your ServiceNow instance according to your organization's needs ? Explore the ServiceNow-exposed JavaScript APIs and libraries ? Discover the method for using ServiceNow *ing functions ? Take your ServiceNow experience to the next level by understanding advanced *ing ? Learn to build, test, and debug custom applications ? Use your customized instance efficiently with the help of best practices In Detail Industry giants like RedHat and NetApp have adopted ServiceNow for their operational needs, and it is evolving as the number one platform choice for IT Service management. ServiceNow provides their clients with an add-on when it comes to baseline instances, where *ing can be used to customize and improve the performance of instances. It also provides inbuilt JavaScript API for *ing and improving your JavaScript instance. This book will initially cover the basics of ServiceNow *ing and the appropriate time to * in a ServiceNow environment. Then, we dig deeper into client-side and server-side *ing using JavaScipt API. We will also cover advance concepts like on-demand functions, * actions, and best practices. Mastering ServiceNow Scripting acts as an end-to-end guide for writing, testing, and debugging *s of ServiceNow. We cover update sets for moving customizations between ServiceNow instances, jelly *s for making custom pages, and best practices for all types of * in ServiceNow. By the end of this book, you will have hands-on experience in *ing ServiceNow using inbuilt JavaScript API. Style and approach The book will take a practical approach delving into different aspects of ServiceNow *ing to help you become a *ing master.

Leverage the power of machine learning and Swift programming to build intelligent iOS applications with ease About This Book ? Implement effective machine learning solutions for your iOS applications ? Use Swift and Core ML to build and deploy popular machine learning models ? Develop neural networks for natural language processing and computer vision Who This Book Is For iOS developers who wish to create smarter iOS applications using the power of machine learning will find this book to be useful. This book will also benefit data science professionals who are interested in performing machine learning on mobile devices. Familiarity with Swift programming is all you need to get started with this book. What You Will Learn ? Learn rapid model prototyping with Python and Swift ? Deploy pre-trained models to iOS using Core ML ? Find hidden patterns in the data using unsupervised learning ? Get a deeper understanding of the clustering techniques ? Learn modern compact architectures of neural networks for iOS devices ? Train neural networks for image processing and natural language processing In Detail Machine learning as a field promises to bring increased intelligence to the software by helping us learn and analyse information efficiently and discover certain patterns that humans cannot. This book will be your guide as you embark on an exciting journey in machine learning using the popular Swift language. We’ll start with machine learning basics in the first part of the book to develop a lasting intuition about fundamental machine learning concepts. We explore various supervised and unsupervised statistical learning techniques and how to implement them in Swift, while the third section walks you through deep learning techniques with the help of typical real-world cases. In the last section, we will dive into some hard core topics such as model compression, GPU acceleration and provide some recommendations to avoid common mistakes during machine learning application development. By the end of the book, you'll be able to develop intelligent applications written in Swift that can learn for themselves. Style and approach A comprehensive guide that teaches how to implement machine learning apps for iOS from scratch

Learn how to model and train advanced neural networks to implement a variety of Computer Vision tasks About This Book ? Train different kinds of deep learning model from scratch to solve specific problems in Computer Vision ? Combine the power of Python, Keras, and TensorFlow to build deep learning models for object detection, image classification, similarity learning, image captioning, and more ? Includes tips on optimizing and improving the performance of your models under various constraints Who This Book Is For This book is targeted at data scientists and Computer Vision practitioners who wish to apply the concepts of Deep Learning to overcome any problem related to Computer Vision. A basic knowledge of programming in Python—and some understanding of machine learning concepts—is required to get the best out of this book. What You Will Learn ? Set up an environment for deep learning with Python, TensorFlow, and Keras ? Define and train a model for image and video classification ? Use features from a pre-trained Convolutional Neural Network model for image retrieval ? Understand and implement object detection using the real-world Pedestrian Detection scenario ? Learn about various problems in image captioning and how to overcome them by training images and text together ? Implement similarity matching and train a model for face recognition ? Understand the concept of generative models and use them for image generation ? Deploy your deep learning models and optimize them for high performance In Detail Deep learning has shown its power in several application areas of Artificial Intelligence, especially in Computer Vision. Computer Vision is the science of understanding and manipulating images, and finds enormous applications in the areas of robotics, automation, and so on. This book will also show you, with practical examples, how to develop Computer Vision applications by leveraging the power of deep learning. In this book, you will learn different techniques related to object classification, object detection, image segmentation, captioning, image generation, face analysis, and more. You will also explore their applications using popular Python libraries such as TensorFlow and Keras. This book will help you master state-of-the-art, deep learning algorithms and their implementation. Style and approach This book will teach advanced techniques for Computer Vision, applying the deep learning model in reference to various datasets.

Design, build and test RESTful web services with the Django framework and Python About This Book ? Create efficient real-world RESTful web services with the latest Django framework ? Authenticate, secure, and integrate third-party packages efficiently in your Web Services ? Leverage the power of Python for faster Web Service development Who This Book Is For This book is for Python developers who want to create RESTful web services with Django; you need to have a basic working knowledge of Django but no previous experience with RESTful web services is required. What You Will Learn ? The best way to build a RESTful Web Service or API with Django and the Django REST Framework ? Develop complex RESTful APIs from scratch with Django and the Django REST Framework ? Work with either SQL or NoSQL data sources ? Design RESTful Web Services based on application requirements ? Use third-party packages and extensions to perform common tasks ? Create automated tests for RESTful web services ? Debug, test, and profile RESTful web services with Django and the Django REST Framework In Detail Django is a Python web framework that makes the web development process very easy. It reduces the amount of trivial code, which simplifies the creation of web applications and results in faster development. It is very powerful and a great choice for creating RESTful web services. If you are a Python developer and want to efficiently create RESTful web services with Django for your apps, then this is the right book for you. The book starts off by showing you how to install and configure the environment, required software, and tools to create RESTful web services with Django and the Django REST framework. We then move on to working with advanced serialization and migrations to interact with SQLite and non-SQL data sources. We will use the features included in the Django REST framework to improve our simple web service. Further, we will create API views to process diverse HTTP requests on objects, go through relationships and hyperlinked API management, and then discover the necessary steps to include security and permissions related to data models and APIs. We will also apply throttling rules and run tests to check that versioning works as expected. Next we will run automated tests to improve code coverage. By the end of the book, you will be able to build RESTful web services with Django." Style and approach The book takes a straightforward approach, giving you the techniques and best use cases to build great web services with Django and Python

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.

Get more from your network by securing its infrastructure and increasing its effectiveness About This Book ? Learn to choose the best network scanning toolset for your system ? Implement different concepts of network scanning such as port scanning and OS detection ? Adapt a practical approach to securing your network Who This Book Is For If you are a security professional who is responsible for securing an organization's infrastructure, then this book is for you. What You Will Learn ? Achieve an effective security posture to design security architectures ? Learn vital security aspects before moving to the Cloud ? Launch secure applications with Web Application Security and SQL Injection ? Explore the basics of threat detection/response/ mitigation with important use cases ? Learn all about integration principles for PKI and tips to secure it ? Design a WAN infrastructure and ensure security over a public WAN In Detail Network scanning is the process of assessing a network to identify an active host network; same methods can be used by an attacker or network administrator for security assessment. This procedure plays a vital role in risk assessment programs or while preparing a security plan for your organization. Practical Network Scanning starts with the concept of network scanning and how organizations can benefit from it. Then, going forward, we delve into the different scanning steps, such as service detection, firewall detection, TCP/IP port detection, and OS detection. We also implement these concepts using a few of the most prominent tools on the market, such as Nessus and Nmap. In the concluding chapters, we prepare a complete vulnerability assessment plan for your organization. By the end of this book, you will have hands-on experience in performing network scanning using different tools and in choosing the best tools for your system. Style and approach A practical guide that offers a simple way to easily understand network security concepts and apply them to strengthen your network.

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

Leverage Office 365 to increase your organization's efficiency About This Book ? Perform common to advanced-level management and administrative tasks for your organization with Office 365 ? Become an Office 365 generalist who can work with the entire stack—not just specific products ? An advanced-level guide that will teach you to implement enterprise-level services into your organization, no matter the size of the business Who This Book Is For This book targets architects, sys admins, engineers, and administrators who are working with Office 365 and are responsible for configuring, implementing, and managing Office 365 in their organization. A prior knowledge of Office 365 and Exchange servers is mandatory. What You Will Learn ? Get an understanding of the vast Office 365 feature set ? Learn how workloads and applications interact and integrate with each other ? Connect PowerShell to various Office 365 services and perform tasks ? Learn to manage Skype for Business Online ? Get support and monitor Office 365 service health ? Manage and administer identities and groups efficiently In Detail In today's world, every organization aims to migrate to the cloud to become more efficient by making full use of the latest technologies. Office 365 is your one-stop solution to making your organization reliable, scalable, and fast. The book will start with an overview of Office 365 components, and help you learn how to use the administration portal, and perform basic administration. Then this book covers common management tasks such as managing users, admin roles, groups, securing Office 365, and enforcing compliance. In the next set of chapters, you will learn topics such as managing Skype for Business Online, Yammer, OneDrive for Business, and Microsoft Teams. In the final section of the book, you will learn how to perform reporting and monitor Office 365 service health. By the end of this book, you will be able to implement enterprise-level services with Office 365 based on your organization's needs. Style and approach A practical guide that offers a simple way to easily understand and access common administration tasks, without getting lost in the plethora of online resources, support pages, blog posts, and videos.

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.

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.

Create interactive cross-platform games with the Godot Engine 3.0 About This Book ? Learn the art of developing cross-platform games ? Leverage Godot’s node and scene system to design robust, reusable game objects ? Integrate Blender easily and efficiently with Godot to create powerful 3D games Who This Book Is For Godot Engine Game Development Projects is for both new users and experienced developers, who want to learn to make games using a modern game engine. Some prior programming experience is recommended. What You Will Learn ? Get started with the Godot game engine and editor ? Organize a game project ? Import graphical and audio assets ? Use Godot’s node and scene system to design robust, reusable game objects ? Write code in GDScript to capture input and build complex behaviors ? Implement user interfaces to display information ? Create visual effects to spice up your game ? Learn techniques that you can apply to your own game projects In Detail Godot Engine Game Development Projects is an introduction to the Godot game engine and its new 3.0 version. Godot 3.0 brings a large number of new features and capabilities that make it a strong alternative to expensive commercial game engines. For beginners, Godot offers a friendly way to learn game development techniques, while for experienced developers it is a powerful, customizable tool that can bring your visions to life. This book consists of five projects that will help developers achieve a sound understanding of the engine when it comes to building games. Game development is complex and involves a wide spectrum of knowledge and skills. This book can help you build on your foundation level skills by showing you how to create a number of small-scale game projects. Along the way, you will learn how Godot works and discover important game development techniques that you can apply to your projects. Using a straightforward, step-by-step approach and practical examples, the book will take you from the absolute basics through to sophisticated game physics, animations, and other techniques. Upon completing the final project, you will have a strong foundation for future success with Godot 3.0. Style and approach The book is divided into five parts; each covering a different small-game project using a straightforward, step-by-step approach and practical examples. The book will take readers from the absolute basics through sophisticated game physics, animation, and other techniques.

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

Work with Python and powerful open source tools such as Gensim and spaCy to perform modern text analysis, natural language processing, and computational linguistics algorithms. About This Book ? Discover the open source Python text analysis ecosystem, using spaCy, Gensim, scikit-learn, and Keras ? Hands-on text analysis with Python, featuring natural language processing and computational linguistics algorithms ? Learn deep learning techniques for text analysis Who This Book Is For This book is for you if you want to dive in, hands-first, into the interesting world of text analysis and NLP, and you're ready to work with the rich Python ecosystem of tools and datasets waiting for you! What You Will Learn ? Why text analysis is important in our modern age ? Understand NLP terminology and get to know the Python tools and datasets ? Learn how to pre-process and clean textual data ? Convert textual data into vector space representations ? Using spaCy to process text ? Train your own NLP models for computational linguistics ? Use statistical learning and Topic Modeling algorithms for text, using Gensim and scikit-learn ? Employ deep learning techniques for text analysis using Keras In Detail Modern text analysis is now very accessible using Python and open source tools, so discover how you can now perform modern text analysis in this era of textual data. This book shows you how to use natural language processing, and computational linguistics algorithms, to make inferences and gain insights about data you have. These algorithms are based on statistical machine learning and artificial intelligence techniques. The tools to work with these algorithms are available to you right now - with Python, and tools like Gensim and spaCy. You'll start by learning about data cleaning, and then how to perform computational linguistics from first concepts. You're then ready to explore the more sophisticated areas of statistical NLP and deep learning using Python, with realistic language and text samples. You'll learn to tag, parse, and model text using the best tools. You'll gain hands-on knowledge of the best frameworks to use, and you'll know when to choose a tool like Gensim for topic models, and when to work with Keras for deep learning. This book balances theory and practical hands-on examples, so you can learn about and conduct your own natural language processing projects and computational linguistics. You'll discover the rich ecosystem of Python tools you have available to conduct NLP - and enter the interesting world of modern text analysis. Style and approach The book teaches NLP from the angle of a practitioner as well as that of a student. This is a tad unusual, but given the enormous speed at which new algorithms and approaches travel from scientific beginnings to industrial implementation, first principles can be clarified with the help of entirely practical examples.

Build effective RESTful APIs for enterprise with design patterns and REST framework’s out-of-the-box capabilities Key Features * Understand advanced topics such as API gateways, API securities, and cloud * Implement patterns programmatically with easy-to-follow examples * Modernize legacy codebase using API connectors, layers, and microservices Book Description This book deals with the Representational State Transfer (REST) paradigm, which is an architectural style that allows networked devices to communicate with each other over the internet. With the help of this book, you’ll explore the concepts of service-oriented architecture (SOA), event-driven architecture (EDA), and resource-oriented architecture (ROA). This book covers why there is an insistence for high-quality APIs toward enterprise integration. It also covers how to optimize and explore endpoints for microservices with API gateways and touches upon integrated platforms and Hubs for RESTful APIs. You’ll also understand how application delivery and deployments can be simplified and streamlined in the REST world. The book will help you dig deeper into the distinct contributions of RESTful services for IoT analytics and applications. Besides detailing the API design and development aspects, this book will assist you in designing and developing production-ready, testable, sustainable, and enterprise-grade APIs. By the end of the book, you’ll be empowered with all that you need to create highly flexible APIs for next-generation RESTful services and applications. What you will learn * Explore RESTful concepts, including URI, HATEOAS, and Code on Demand * Study core patterns like Statelessness, Pagination, and Discoverability * Optimize endpoints for linked microservices with API gateways * Delve into API authentication, authorization, and API security implementations * Work with Service Orchestration to craft composite and process-aware services * Expose RESTful protocol-based APIs for cloud computing Who this book is for This book is primarily for web, mobile, and cloud services developers, architects, and consultants who want to build well-designed APIs for creating and sustaining enterprise-class applications. You’ll also benefit from this book if you want to understand the finer details of RESTful APIs and their design techniques along with some tricks and tips.

Leverage the power of PostgreSQL 11 to build powerful database and data warehousing applications Key Features * Monitor, secure, and fine-tune your PostgreSQL 11 database * Learn client-side and server-side programming using SQL and PL/pgSQL * Discover tips on implementing efficient database solutions Book Description PostgreSQL is one of the most popular open source database management systems in the world, and it supports advanced features included in SQL standards. This book will familiarize you with the latest features in PostgreSQL 11, and get you up and running with building efficient PostgreSQL database solutions from scratch. Learning PostgreSQL, 11 begins by covering the concepts of relational databases and their core principles. You’ll explore the Data Definition Language (DDL) and commonly used DDL commands supported by ANSI SQL. You’ll also learn how to create tables, define integrity constraints, build indexes, and set up views and other schema objects. As you advance, you’ll come to understand Data Manipulation Language (DML) and server-side programming capabilities using PL/pgSQL, giving you a robust background to develop, tune, test, and troubleshoot your database application. The book will guide you in exploring NoSQL capabilities and connecting to your database to manipulate data objects. You’ll get to grips with using data warehousing in analytical solutions and reports, and scaling the database for high availability and performance. By the end of this book, you’ll have gained a thorough understanding of PostgreSQL 11 and developed the necessary skills to build efficient database solutions. What you will learn * Understand the basics of relational databases, relational algebra, and data modeling * Install a PostgreSQL server, create a database, and implement your data model * Create tables and views, define indexes and stored procedures, and implement triggers * Make use of advanced data types such as Arrays, hstore, and JSONB * Connect your Python applications to PostgreSQL and work with data efficiently * Identify bottlenecks to enhance reliability and performance of database applications Who this book is for This book is for you if you're interested in learning about PostgreSQL from scratch. Those looking to build solid database or data warehousing applications or wanting to get up to speed with the latest features of PostgreSQL 11 will also find this book useful. No prior knowledge of database programming or administration is required to get started.