Foster your NLP applications with the help of deep learning, NLTK, and TensorFlow Key Features * Weave neural networks into linguistic applications across various platforms * Perform NLP tasks and train its models using NLTK and TensorFlow * Boost your NLP models with strong deep learning architectures such as CNNs and RNNs Book Description Natural language processing (NLP) has found its application in various domains, such as web search, advertisements, and customer services, and with the help of deep learning, we can enhance its performances in these areas. Hands-On Natural Language Processing with Python teaches you how to leverage deep learning models for performing various NLP tasks, along with best practices in dealing with today’s NLP challenges. To begin with, you will understand the core concepts of NLP and deep learning, such as Convolutional Neural Networks (CNNs), recurrent neural networks (RNNs), semantic embedding, Word2vec, and more. You will learn how to perform each and every task of NLP using neural networks, in which you will train and deploy neural networks in your NLP applications. You will get accustomed to using RNNs and CNNs in various application areas, such as text classification and sequence labeling, which are essential in the application of sentiment analysis, customer service chatbots, and anomaly detection. You will be equipped with practical knowledge in order to implement deep learning in your linguistic applications using Python's popular deep learning library, TensorFlow. By the end of this book, you will be well versed in building deep learning-backed NLP applications, along with overcoming NLP challenges with best practices developed by domain experts. What you will learn *Implement semantic embedding of words to classify and find entities *Convert words to vectors by training in order to perform arithmetic operations *Train a deep learning model to detect classification of tweets and news *Implement a question-answer model with search and RNN models *Train models for various text classification datasets using CNN *Implement WaveNet a deep generative model for producing a natural-sounding voice *Convert voice-to-text and text-to-voice *Train a model to convert speech-to-text using DeepSpeech Who this book is for Hands-on Natural Language Processing with Python is for you if you are a developer, machine learning or an NLP engineer who wants to build a deep learning application that leverages NLP techniques. This comprehensive guide is also useful for deep learning users who want to extend their deep learning skills in building NLP applications. All you need is the basics of machine learning and Python to enjoy the book.

Develop modern user interfaces using Angular 6 and its component-based architecture. Key Features * Build better web applications with highly scalable concepts using Angular * Learn new ways to design your web applications * Build a fully functional web application that lets you tackle real-world user interface problems using Angular components Book Description Angular framework embraces a mature user interface (UI) component architecture, a powerful tool when developing scalable application interfaces. The simple and deterministic design of Angular components supports you in building large and scalable component-based applications. Mastering Angular Components covers a new holistic way of thinking about UI development, and helps you discover the power of Angular 6 components through various examples. The book starts with an introduction to component-based user interfaces and how Angular 6 manages this concept. Following a step-by-step approach, you will build a fully functional task-management application using Angular. You’ll start with basic layout components, adding some core task-management components before completing the first draft of your application. You will then move on to working through a refactoring exercise in order to learn how to enhance the way you deal with states and data. Once you have got to grips with all this, you will study how to make use of the Angular router within your application. By the end of this book, you will be able to constantly refine the functionality of your application and create components that render SVG graphics, add a time-tracking feature, visualize data using third-party library Chartist, and even create a plugin architecture using Angular components. What you will learn * Use TypeScript to create Angular 6 components * Leverage component composition to solve complex UI requirements * Build an architecture using pure components and container components * Explore the basics of RxJS observable streams and use them to build your application reactively * Communicate between components using child queries * Implement the Angular router to make your application navigable * Build reusable and dynamic graphical content using Angular components and SVG * Integrate third-party libraries such as Moment.js and Chartist into your existing Angular application Who this book is for Mastering Angular Components is for you if you are an Angular developer who already has a good understanding of basic frontend web technologies such as JavaScript, HTML, and CSS.

Deploy functions efficiently using different cloud-based serverless offerings Key Features *Understand the concept of Function-as-a-Service *Implement Serverless solutions using AWS Lambda, Azure Functions and Google Cloud Functions *Practical approach towards choosing the best tool for your serverless environment Book Description Serverless applications and architectures are gaining momentum and are increasingly being used by companies of all sizes. Serverless software takes care of many problems that developers face when running systems and servers, such as fault tolerance, centralized logging, horizontal scalability, and deployments. You will learn how to harness serverless technology to rapidly reduce production time and minimize your costs, while still having the freedom to customize your code, without hindering functionality. Upon finishing the book, you will have the knowledge and resources to build your own serverless application hosted in AWS, Microsoft Azure, or Google Cloud Platform, and will have experienced the benefits of event-driven technology for yourself. This hands-on guide dives into the basis of serverless architectures and how to build them using Node.js as a programming language, Visual Studio Code for code editing, and Postman for quickly and securely developing applications without the hassle of configuring and maintaining infrastructure on three public cloud platforms. What you will learn *Understand the benefts of serverless computing and know when to use it *Develop serverless applications on AWS, Azure, and Google Cloud *Get to grips with Function as a Service (FaaS) *Apply triggers to serverless functions *Build event-driven apps using serverless frameworks *Use the Node.js programming language to build serverless apps *Use code editors, such as Visual Studio Code, as development environments *Master the best development practices for creating scalable and practical solutions Who this book is for This book is targeted towards developers, system administrators or any stakeholder working in the Serverless environment and want to understand how functions work. Basic idea of serverless architecture can be an added advantage

Master realistic animations and graphics, particle systems, game AI and physics, sprites and VR development with Unity 2017 About This Book ? Create professional grade games with realistic animation and graphics, particle systems and game physics with Unity 2017 ? Unleash the power of C# *ing to create intelligent game AI and professional grade game workflows. ? Create immersive VR games using the latest Unity 2017 VR SDK. Who This Book Is For If you are a Unity developer who now wants to develop and deploy interesting games by leveraging the new features of Unity 2017, then this is the book for you. Basic knowledge of C# programming is assumed. What You Will Learn ? Explore hands-on tasks and real-world scenarios to make a Unity horror adventure game ? Create enemy characters that act intelligently and make reasoned decisions ? Use data files to save and restore game data in a way that is platform-agnostic ? Get started with VR development ? Use navigation meshes, occlusion culling, and Profiler tools ? Work confidently with GameObjects, rotations, and transformations ? Understand specific gameplay features such as AI enemies, inventory systems, and level design In Detail Do you want to make the leap from being an everyday Unity developer to being a pro game developer? Then look no further! This book is your one-stop solution to creating mesmerizing games with lifelike features and amazing gameplay. This book focuses in some detail on a practical project with Unity, building a first-person game with many features. You'll delve into the architecture of a Unity game, creating expansive worlds, interesting render effects, and other features to make your games special. You will create individual game components, use efficient animation techniques, and implement collision and physics effectively. Specifically, we'll explore optimal techniques for importing game assets, such as meshes and textures; tips and tricks for effective level design; how to animate and * NPCs; how to configure and deploy to mobile devices; how to prepare for VR development; how to work with version control; and more. By the end of this book, you'll have developed sufficient competency in Unity development to produce fun games with confidence. Style and approach This book takes an easy-to-follow, step-by-step tutorial approach. You will create an advanced level Unity game with an emphasis on leveraging advanced Unity 2017 features while developing the game in its entirety.

Getting started with the processes and the tools to continuously deliver high-quality software About This Book ? Incorporate popular development practices to prevent messy code ? Automate your build, integration, release, and deployment processes with Jenkins, Git, and Gulp―and learn how continuous integration (CI) can save you time and money ? Gain an end-to-end overview of Continuous Integration using different languages (JavaScript and C#) and tools (Gulp and Jenkins) Who This Book Is For This book is for developers who want to understand and implement Continuous Integration and Delivery in their daily work. A basic knowledge of at least JavaScript and HTML/CSS is required. Knowing C# and SQL will come in handy. Most programmers who have programmed in a (compiled) C-like language will be able to follow along. What You Will Learn ? Get to know all the aspects of Continuous Integration, Deployment, and Delivery ? Find out how Git can be used in a CI environment ? Set up browser tests using Karma and Selenium and unit tests using Jasmine ? Use Node.js, npm, and Gulp to automate tasks such as linting, testing, and minification ? Explore different Jenkins jobs to integrate with Node.js and C# projects ? Perform Continuous Delivery and Deployment using Jenkins ? Test and deliver a web API In Detail The challenge faced by many teams while implementing Continuous Deployment is that it requires the use of many tools and processes that all work together. Learning and implementing all these tools (correctly) takes a lot of time and effort, leading people to wonder whether it's really worth it. This book sets up a project to show you the different steps, processes, and tools in Continuous Deployment and the actual problems they solve. We start by introducing Continuous Integration (CI), deployment, and delivery as well as providing an overview of the tools used in CI. You'll then create a web app and see how Git can be used in a CI environment. Moving on, you'll explore unit testing using Jasmine and browser testing using Karma and Selenium for your app. You'll also find out how to automate tasks using Gulp and Jenkins. Next, you'll get acquainted with database integration for different platforms, such as MongoDB and PostgreSQL. Finally, you'll set up different Jenkins jobs to integrate with Node.js and C# projects, and Jenkins pipelines to make branching easier. By the end of the book, you'll have implemented Continuous Delivery and deployment from scratch. Style and approach This practical book takes a step-by-step approach to explaining all the concepts of Continuous Integration and delivery, and how it can help you deliver a high-quality product.

A comprehensive guide to mastering the art of preventing your Linux system from getting compromised. About This Book ? Leverage this guide to confidently deliver a system that reduces the risk of being hacked ? Perform a number of advanced Linux security techniques such as network service detection, user authentication, controlling special permissions, encrypting file systems, and much more ? Master the art of securing a Linux environment with this end-to-end practical guide Who This Book Is For If you are a systems administrator or a network engineer interested in making your Linux environment more secure, then this book is for you. Security consultants wanting to enhance their Linux security skills will also benefit from this book. Prior knowledge of Linux is mandatory. What You Will Learn ? Use various techniques to prevent intruders from accessing sensitive data ? Prevent intruders from planting malware, and detect whether malware has been planted ? Prevent insiders from accessing data that they aren’t authorized to access ? Do quick checks to see whether a computer is running network services that it doesn’t need to run ? Learn security techniques that are common to all Linux distros, and some that are distro-specific In Detail This book has extensive coverage of techniques that will help prevent attackers from breaching your system, by building a much more secure Linux environment. You will learn various security techniques such as SSH hardening, network service detection, setting up firewalls, encrypting file systems, protecting user accounts, authentication processes, and so on. Moving forward, you will also develop hands-on skills with advanced Linux permissions, access control, special modes, and more. Lastly, this book will also cover best practices and troubleshooting techniques to get your work done efficiently. By the end of this book, you will be confident in delivering a system that will be much harder to compromise. Style and approach An advanced-level guide filled with real-world examples that will help you secure your Linux system

Build, scale, and deploy deep neural network models using the star libraries in Python About This Book ? Delve into advanced machine learning and deep learning use cases using Tensorflow and Keras ? Build, deploy, and scale end-to-end deep neural network models in a production environment ? Learn to deploy TensorFlow on mobile, and distributed TensorFlow on GPU, Clusters, and Kubernetes Who This Book Is For This book is for data scientists, machine learning engineers, artificial intelligence engineers, and for all TensorFlow users who wish to upgrade their TensorFlow knowledge and work on various machine learning and deep learning problems. If you are looking for an easy-to-follow guide that underlines the intricacies and complex use cases of machine learning, you will find this book extremely useful. Some basic understanding of TensorFlow is required to get the most out of the book. What You Will Learn ? Master advanced concepts of deep learning such as transfer learning, reinforcement learning, generative models and more, using TensorFlow and Keras ? Perform supervised (classification and regression) and unsupervised (clustering) learning to solve machine learning tasks ? Build end-to-end deep learning (CNN, RNN, and Autoencoders) models with TensorFlow ? Scale and deploy production models with distributed and high-performance computing on GPU and clusters ? Build TensorFlow models to work with multilayer perceptrons using Keras, TFLearn, and R ? Learn the functionalities of smart apps by building and deploying TensorFlow models on iOS and Android devices ? Supercharge TensorFlow with distributed training and deployment on Kubernetes and TensorFlow Clusters In Detail TensorFlow is the most popular numerical computation library built from the ground up for distributed, cloud, and mobile environments. TensorFlow represents the data as tensors and the computation as graphs. This book is a comprehensive guide that lets you explore the advanced features of TensorFlow 1.x. Gain insight into TensorFlow Core, Keras, TF Estimators, TFLearn, TF Slim, Pretty Tensor, and Sonnet. Leverage the power of TensorFlow and Keras to build deep learning models, using concepts such as transfer learning, generative adversarial networks, and deep reinforcement learning. Throughout the book, you will obtain hands-on experience with varied datasets, such as MNIST, CIFAR-10, PTB, text8, and COCO-Images. You will learn the advanced features of TensorFlow1.x, such as distributed TensorFlow with TF Clusters, deploy production models with TensorFlow Serving, and build and deploy TensorFlow models for mobile and embedded devices on Android and iOS platforms. You will see how to call TensorFlow and Keras API within the R statistical software, and learn the required techniques for debugging when the TensorFlow API-based code does not work as expected. The book helps you obtain in-depth knowledge of TensorFlow, making you the go-to person for solving artificial intelligence problems. By the end of this guide, you will have mastered the offerings of TensorFlow and Keras, and gained the skills you need to build smarter, faster, and efficient machine learning and deep learning systems. Style and approach Step-by-step comprehensive guide filled with advanced, real-world examples to help you master Tensorflow 1.x

Create fast and efficient server-side applications using the latest features of Odoo v11 About This Book ? Get the most up-to-date guide on Odoo 11 to create custom and reusable modules ? Interconnect your application with other systems by implementing web APIs ? Understand the mechanisms powering the Odoo framework to build robust enterprises Who This Book Is For If you're a Python developer and want to develop highly efficient business applications with the latest Odoo framework (or if you just want a hands on problem solution book for all your Odoo Development related issues), this book is for you! Some experience with the JavaScript programming language and web development is required to get the most out of this book. What You Will Learn ? Install and manage Odoo environments and instances ? Use models to define your application's data structures ? Add business logic to your applications ? Add automated tests and learn how to debug Odoo apps ? Learn about the access security model and internationalization features ? Customize websites built with Odoo, by writing your own templates and providing new snippets for use in the website builder ? Extend the web client with new widgets and make RPC calls to the server In Detail Odoo is a full-featured open source ERP with a focus on extensibility. The flexibility and sustainability of open source are also a key selling point of Odoo. It is built on a powerful framework for rapid application development, both for back-end applications and front-end websites. Version 11 offers better usability and speed: a new design (as compared to the current Odoo Enterprise version) and a mobile interface. The book starts by covering Odoo installation and administration and Odoo Server deployment. It then delves into the implementation of Odoo modules, the different inheritance models available in Odoo. You will then learn how to define access rules for your data; how to make your application available in different languages; how to expose your data models to end users on the back end and on the front end; and how to create beautiful PDF versions of your data. By the end of the book, you will have a thorough knowledge of Odoo and will be able to build effective applications by applying Odoo development best practices Style and Approach This recipe-based practical guide presents each topic with step-by-step instructions on how you can create fast and efficient server-side applications using the latest features of Odoo v11

Learn to design, implement and secure your IoT infrastructure About This Book ? Build a complete IoT system that is the best fit for your organization ? Learn about different concepts, technologies, and tradeoffs in the IoT architectural stack ? Understand the theory, concepts, and implementation of each element that comprises IoT design—from sensors to the cloud ? Implement best practices to ensure the reliability, scalability, robust communication systems, security, and data analysis in your IoT infrastructure Who This Book Is For This book is for architects, system designers, technologists, and technology managers who want to understand the IoT ecosphere, various technologies, and tradeoffs and develop a 50,000-foot view of IoT architecture. What You Will Learn ? Understand the role and scope of architecting a successful IoT deployment, from sensors to the cloud ? Scan the landscape of IoT technologies that span everything from sensors to the cloud and everything in between ? See the trade-offs in choices of protocols and communications in IoT deployments ? Build a repertoire of skills and the vernacular necessary to work in the IoT space ? Broaden your skills in multiple engineering domains necessary for the IoT architect In Detail The Internet of Things (IoT) is the fastest growing technology market. Industries are embracing IoT technologies to improve operational expenses, product life, and people's well-being. An architectural guide is necessary if you want to traverse the spectrum of technologies needed to build a successful IoT system, whether that's a single device or millions of devices. This book encompasses the entire spectrum of IoT solutions, from sensors to the cloud. We start by examining modern sensor systems and focus on their power and functionality. After that, we dive deep into communication theory, paying close attention to near-range PAN, including the new Bluetooth? 5.0 specification and mesh networks. Then, we explore IP-based communication in LAN and WAN, including 802.11ah, 5G LTE cellular, SigFox, and LoRaWAN. Next, we cover edge routing and gateways and their role in fog computing, as well as the messaging protocols of MQTT and CoAP. With the data now in internet form, you'll get an understanding of cloud and fog architectures, including the OpenFog standards. We wrap up the analytics portion of the book with the application of statistical analysis, complex event processing, and deep learning models. Finally, we conclude by providing a holistic view of the IoT security stack and the anatomical details of IoT exploits while countering them with software defined perimeters and blockchains. Style and approach This hands-on guide combines theory and application to the Internet of Things. This book covers the entire architectural stack of components and engineering domains from sensors to power analysis, communication systems, information theory, networking and routing, data security, protocols, software stacks, cloud mechanics, and data analytics with deep learning.

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.

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.

Powerful smart applications using deep learning algorithms to dominate numerical computing, deep learning, and functional programming. About This Book ? Explore machine learning techniques with prominent open source Scala libraries such as Spark ML, H2O, MXNet, Zeppelin, and DeepLearning4j ? Solve real-world machine learning problems by delving complex numerical computing with Scala functional programming in a scalable and faster way ? Cover all key aspects such as collection, storing, processing, analyzing, and evaluation required to build and deploy machine models on computing clusters using Scala Play framework. Who This Book Is For If you want to leverage the power of both Scala and Spark to make sense of Big Data, then this book is for you. If you are well versed with machine learning concepts and wants to expand your knowledge by delving into the practical implementation using the power of Scala, then this book is what you need! Strong understanding of Scala Programming language is recommended. Basic familiarity with machine Learning techniques will be more helpful. What You Will Learn ? Apply advanced regression techniques to boost the performance of predictive models ? Use different classification algorithms for business analytics ? Generate trading strategies for Bitcoin and stock trading using ensemble techniques ? Train Deep Neural Networks (DNN) using H2O and Spark ML ? Utilize NLP to build scalable machine learning models ? Learn how to apply reinforcement learning algorithms such as Q-learning for developing ML application ? Learn how to use autoencoders to develop a fraud detection application ? Implement LSTM and CNN models using DeepLearning4j and MXNet In Detail Machine learning has had a huge impact on academia and industry by turning data into actionable information. Scala has seen a steady rise in adoption over the past few years, especially in the fields of data science and analytics. This book is for data scientists, data engineers, and deep learning enthusiasts who have a background in complex numerical computing and want to know more hands-on machine learning application development. If you're well versed in machine learning concepts and want to expand your knowledge by delving into the practical implementation of these concepts using the power of Scala, then this book is what you need! Through 11 end-to-end projects, you will be acquainted with popular machine learning libraries such as Spark ML, H2O, DeepLearning4j, and MXNet. At the end, you will be able to use numerical computing and functional programming to carry out complex numerical tasks to develop, build, and deploy research or commercial projects in a production-ready environment. Style and approach Leverage the power of machine learning and deep learning in different domains, giving best practices and tips from a real world case studies and help you to avoid pitfalls and fallacies towards decision making based on predictive analytics with ML models.

Write code that scales across CPU registers, multi-core, and machine clusters About This Book ? Explore concurrent programming in C++ ? Identify memory management problems ? Use SIMD and STL containers for performance improvement Who This Book Is For If you're a C++ developer looking to improve the speed of your code or simply wanting to take your skills up to the next level, then this book is perfect for you. What You Will Learn ? Find out how to use exciting new tools that will help you improve your code ? Identify bottlenecks to optimize your code ? Develop applications that utilize GPU computation ? Reap the benefits of concurrent programming ? Write code that can protect against application errors using error handling ? Use STL containers and algorithms effciently ? Extend your toolbox with Boost containers ? Achieve effcient memory management by using custom memory allocators In Detail C++ is a highly portable language and can be used to write complex applications and performance-critical code. It has evolved over the last few years to become a modern and expressive language. This book will guide you through optimizing the performance of your C++ apps by allowing them to run faster and consume fewer resources on the device they're running on. The book begins by helping you to identify the bottlenecks in C++. It then moves on to measuring performance, and you'll see how this affects the way you write code. Next, you'll see the importance of data structure optimization and how it can be used efficiently. After that, you'll see which algorithm should be used to achieve faster execution, followed by how to use STL containers. Moving on, you'll learn how to improve memory management in C++. You'll get hands on experience making use of multiple cores to enable more efficient and faster execution. The book ends with a brief overview of utilizing the capabilities of your GPU by using Boost Compute and OpenCL. Style and approach This easy-to-follow guide is full of examples and self-sufficient code snippets that help you with high performance programming with C++. You’ll get your hands dirty with this all-inclusive guide that uncovers hidden performance improvement areas for any C++ code.

Blend the power of Qt with OpenCV to build cross-platform computer vision applications About This Book ? Start creating robust applications with the power of OpenCV and Qt combined ? Learn from scratch how to develop cross-platform computer vision applications ? Accentuate your OpenCV applications by developing them with Qt Who This Book Is For This book is for readers interested in building computer vision applications. Intermediate knowledge of C++ programming is expected. Even though no knowledge of Qt5 and OpenCV 3 is assumed, if you’re familiar with these frameworks, you’ll benefit. What You Will Learn ? Get an introduction to Qt IDE and SDK ? Be introduced to OpenCV and see how to communicate between OpenCV and Qt ? Understand how to create UI using Qt Widgets ? Know to develop cross-platform applications using OpenCV 3 and Qt 5 ? Explore the multithreaded application development features of Qt5 ? Improve OpenCV 3 application development using Qt5 ? Build, test, and deploy Qt and OpenCV apps, either dynamically or statically ? See Computer Vision technologies such as filtering and transformation of images, detecting and matching objects, template matching, object tracking, video and motion analysis, and much more ? Be introduced to QML and Qt Quick for iOS and Android application development In Detail Developers have been using OpenCV library to develop computer vision applications for a long time. However, they now need a more effective tool to get the job done and in a much better and modern way. Qt is one of the major frameworks available for this task at the moment. This book will teach you to develop applications with the combination of OpenCV 3 and Qt5. This book will teach you to create cross-platform computer vision applications. We’ll begin by introducing Qt, its IDE, and its SDK. Next you’ll learn how to use the OpenCV API to integrate both tools, and see how to configure Qt to use OpenCV. You’ll go on to build a full-fledged computer vision application throughout the book. Later, you’ll create a stunning UI application using the Qt widgets technology, where you’ll display the images after they are processed in an efficient way. At the end of the book, you’ll learn how to convert OpenCV Mat to Qt QImage. You’ll also see how to efficiently process images to filter them, transform them, detect or track objects as well as analyze video. You’ll become better at developing OpenCV applications. Style and approach This book will help you understand and create cross-platform and multithreaded computer vision applications with the help of OpenCV 3 and Qt5, using a plugin-based and modular application development approach.

Discover techniques and tools for building serverless applications with AWS About This Book ? Get well-versed with building and deploying serverless APIs with microservices ? Learn to build distributed applications and microservices with AWS Step Functions ? A step-by-step guide that will get you up and running with building and managing applications on the AWS platform Who This Book Is For If you are an I.T. professional or a system architect who wants to improve infrastructure using AWS, then this book is for you. It is also for programmers who are new to AWS and want to build highly efficient, scalable applications. What You Will Learn ? Set up your AWS account and get started with the basic concepts of AWS ? Learn about AWS terminology and identity access management ? Acquaint yourself with important elements of the cloud with features such as computing, ELB, and VPC ? Back up your database and ensure high availability by having an understanding of database-related services in the AWS cloud ? Integrate AWS services with your application to meet and exceed non-functional requirements ? Create and automate infrastructure to design cost-effective, highly available applications In Detail Amazon Web Services (AWS) is the most popular and widely-used cloud platform. Administering and deploying application on AWS makes the applications resilient and robust. The main focus of the book is to cover the basic concepts of cloud-based development followed by running solutions in AWS Cloud, which will help the solutions run at scale. This book not only guides you through the trade-offs and ideas behind efficient cloud applications, but is a comprehensive guide to getting the most out of AWS. In the first section, you will begin by looking at the key concepts of AWS, setting up your AWS account, and operating it. This guide also covers cloud service models, which will help you build highly scalable and secure applications on the AWS platform. We will then dive deep into concepts of cloud computing with S3 storage, RDS and EC2. Next, this book will walk you through VPC, building realtime serverless environments, and deploying serverless APIs with microservices. Finally, this book will teach you to monitor your applications, and automate your infrastructure and deploy with CloudFormation. By the end of this book, you will be well-versed with the various services that AWS provides and will be able to leverage AWS infrastructure to accelerate the development process. Style and approach ? Learn to write, run, and deploy applications in the AWS cloud ? Make the most of AWS to build scalable and cost-efficient systems ? A practical guide to developing serverless services and make the applications run faster

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.

Develop applications for the real world with a thorough software testing approach About This Book ? Develop a thorough understanding of TDD and how it can help you develop simpler applications with no defects using C# and JavaScript ? Adapt to the mindset of writing tests before code by incorporating business goals, code manageability, and other factors ? Make all your software units and modules pass tests by analyzing failed tests and refactoring code as and when required Who This Book Is For This book is for software developers with a basic knowledge of Test Driven Development (TDD) who want a thorough understanding of how TDD can benefit them and the applications they produce. The examples in this book are in C#, and you will need a basic understanding of C# to work through these examples. What You Will Learn ? The core concepts of TDD ? Testing in action with a real-world case study in C# and JavaScript using React ? Writing proper Unit Tests and testable code for your application ? Using different types of test double such as stubs, spies, and mocks ? Growing an application guided by tests ? Exploring new developments on a green-field application ? Mitigating the problems associated with writing tests for legacy applications ? Modifying a legacy application to make it testable In Detail Test-Driven Development (TDD) is a methodology that helps you to write as little as code as possible to satisfy software requirements, and ensures that what you've written does what it's supposed to do. If you're looking for a practical resource on Test-Driven Development this is the book for you. You've found a practical end-to-end guide that will help you implement Test-Driven Techniques for your software development projects. You will learn from industry standard patterns and practices, and shift from a conventional approach to a modern and efficient software testing approach in C# and JavaScript. This book starts with the basics of TDD and the components of a simple unit test. Then we look at setting up the testing framework so that you can easily run your tests in your development environment. You will then see the importance of defining and testing boundaries, abstracting away third-party code (including the .NET Framework), and working with different types of test double such as spies, mocks, and fakes. Moving on, you will learn how to think like a TDD developer when it comes to application development. Next, you'll focus on writing tests for new/changing requirements and covering newly discovered bugs, along with how to test JavaScript applications and perform integration testing. You’ll also learn how to identify code that is inherently un-testable, and identify some of the major problems with legacy applications that weren’t written with testability in mind. By the end of the book, you’ll have all the TDD skills you'll need and you’ll be able to re-enter the world as a TDD expert! Style and approach A practical step-by-step approach with real-world case studies.

Learn how to apply Functional Programming with Kotlin to real-life projects with popular libraries like Arrow. About This Book ? Focus on the functional aspects of Kotlin and identify the advantages that functional programming brings to the table and the associated coding benefits, ? Implement common functional programming design patterns and techniques. ? Learn to combine OOP and Reactive Programming with Functional Programming and how RxKotlin and funkTionale can help you implementing Functional Programming in Kotlin Who This Book Is For Kotlin developers who have no functional programming experience, will benefit from this book. What You Will Learn ? Learn the Concepts of Functional Programming with Kotlin ? Discover the Coroutines in Kotlin ? Uncover Using funkTionale plugin ? Learn Monads, Functiors and Applicatives ? Combine Functional Programming with OOP and Reactive Programming ? Uncover Using Monads with funkTionale ? Discover Stream Processing In Detail Functional programming makes your application faster, improves performance, and increases your productivity. Kotlin supports many of the popular and advanced functional features of functional languages. This book will cover the A-Z of functional programming in Kotlin. This book bridges the language gap for Kotlin developers by showing you how to create and consume functional constructs in Kotlin. We also bridge the domain gap by showing how functional constructs can be applied in business scenarios. We’ll take you through lambdas, pattern matching, immutability, and help you develop a deep understanding of the concepts and practices of functional programming. If you want learn to address problems using Recursion, Koltin has support for it as well. You’ll also learn how to use the funKtionale library to perform currying and lazy programming and more. Finally, you’ll learn functional design patterns and techniques that will make you a better programmer.By the end of the book, you will be more confident in your functional programming skills and will be able to apply them while programming in Kotlin. Style and approach Loaded with numerous code examples and real life projects, this book helps you dive deep into Functional Programming with Kotlin as well as applying it with help of Functional Programming Plugins like funkTionale and RxKotlin.

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.

Learn how to solve blocking user experience and build event based reactive applications with Swift. About This Book ? Build fast and scalable apps with RxSwift ? Apply reactive programming to solve complex problems and build efficient programs with reactive user interfaces ? Take expressiveness, scalability, and maintainability of your Swift code to the next level with this practical guide Who This Book Is For This book is for the developers who are familiar with Swift and iOS application development and are looking out to reduce the complexity of their apps. Prior experience of reactive programming is not necessary. What You Will Learn ? Understand the practical benefits of Rx on a mobile platform ? Explore the building blocks of Rx, and Rx data flows with marble diagrams ? Learn how to convert an existing code base into RxSwift code base ? Learn how to debug and test your Rx Code ? Work with Playgrounds to transform sequences by filtering them using map, flatmap and other operators ? Learn how to combine different operators to work with Events in a more controlled manner. ? Discover RxCocoa and convert your simple UI elements to Reactive components ? Build a complete RxSwift app using MVVM as design pattern In Detail RxSwift belongs to a large family of Rx implementations in different programming languages that share almost identical syntax and semantics. Reactive approach will help you to write clean, cohesive, resilient, scalable, and maintainable code with highly configurable behavior. This book will introduce you to the world of reactive programming, primarily focusing on mobile platforms. It will tell how you can benefit from using RxSwift in your projects, existing or new. Further on, the book will demonstrate the unbelievable ease of configuring asynchronous behavior and other aspects of the app that are traditionally considered to be hard to implement and maintain. It will explain what Rx is made of, and how to switch to reactive way of thinking to get the most out of it. Also, test production code using RxTest and the red/ green approach. Finally, the book will dive into real-world recipes and show you how to build a real-world app by applying the reactive paradigm. By the end of the book, you’ll be able to build a reactive swift application by leveraging all the concepts this book takes you through. Style and approach This book is a definite tutorial in FRP with Swift filled with well-described examples.

One stop guide to implementing award-winning, and cutting-edge CNN architectures About This Book ? Fast-paced guide with use cases and real-world examples to get well versed with CNN techniques ? Implement CNN models on image classification, transfer learning, Object Detection, Instance Segmentation, GANs and more ? Implement powerful use-cases like image captioning, reinforcement learning for hard attention, and recurrent attention models Who This Book Is For This book is for data scientists, machine learning and deep learning practitioners, Cognitive and Artificial Intelligence enthusiasts who want to move one step further in building Convolutional Neural Networks. Get hands-on experience with extreme datasets and different CNN architectures to build efficient and smart ConvNet models. Basic knowledge of deep learning concepts and Python programming language is expected. What You Will Learn ? From CNN basic building blocks to advanced concepts understand practical areas they can be applied to ? Build an image classifier CNN model to understand how different components interact with each other, and then learn how to optimize it ? Learn different algorithms that can be applied to Object Detection, and Instance Segmentation ? Learn advanced concepts like attention mechanisms for CNN to improve prediction accuracy ? Understand transfer learning and implement award-winning CNN architectures like AlexNet, VGG, GoogLeNet, ResNet and more ? Understand the working of generative adversarial networks and how it can create new, unseen images In Detail Convolutional Neural Network (CNN) is revolutionizing several application domains such as visual recognition systems, self-driving cars, medical discoveries, innovative eCommerce and more.You will learn to create innovative solutions around image and video analytics to solve complex machine learning and computer vision related problems and implement real-life CNN models. This book starts with an overview of deep neural networkswith the example of image classification and walks you through building your first CNN for human face detector. We will learn to use concepts like transfer learning with CNN, and Auto-Encoders to build very powerful models, even when not much of supervised training data of labeled images is available. Later we build upon the learning achieved to build advanced vision related algorithms for object detection, instance segmentation, generative adversarial networks, image captioning, attention mechanisms for vision, and recurrent models for vision. By the end of this book, you should be ready to implement advanced, effective and efficient CNN models at your professional project or personal initiatives by working on complex image and video datasets. Style and approach An easy to follow concise and illustrative guide explaining the core concepts of ConvNets to help you understand, implement and deploy your CNN models quickly.