A classic Cold War spy story about the space race from the bestselling thriller writer Derek Lambert. As the Soviet space-shuttle Dove orbits 150 miles above the earth on its maiden flight, Warsaw Pact troops crash into Poland. The seventy-two-year-old President of America wants to be re-elected, and for that he needs to win the first stage of the war in space: he needs to capture the Soviet space shuttle. But as the President plans his coup a nuclear-armed shuttle speeds towards target America – and only defection in space can stop it. ‘Writing as crisp as the Moscow winter … the Soviet setting is magically evocative’ New York Times ‘Lambert, author of many intelligent political thrillers, has another in this fastpaced, complex, and timely novel. Highly recommended’ Library Journal ‘A most satisfying thriller with a highly dramatic finish’ Publishers Weekly

A pragmatic companion guide to your Agile journey About This Book ? Make your team Agile by implementing industry-standard Agile techniques ? Assess scope, scale up efficiently ? Create the correct roles and identify the right candidates for your team ? Finish your projects faster and stay ahead of the curve Who This Book Is For If you’re a software developer or a project manager with little to no experience of Agile, but you want to efficiently implement it, this is the book for you. What You Will Learn ? Create a solid foundation that gives your team an Agile jumpstart ? Understand how to select and evolve practices to increase your team’s agility ? Use experiments to accelerate your team’s understanding ? Fine-tune your approach by incorporating aspects of Lean and Lean Startup ? Know how to foster an environment of continuous improvement and learning that will become self-sustaining In Detail This book will help you overcome the common challenges you’ll face when transforming your working practices from waterfall to Agile. Each chapter builds on the last, starting with easy-to-grasp ways to get going with Agile. Next you’ll see how to choose the right Agile framework for your organization. Moving on, you’ll implement systematic product delivery and measure and report progress with visualization. Then you’ll learn how to create high performing teams, develop people in Agile, manage in Agile, and perform distributed Agile and collaborative governance. At the end of the book, you’ll discover how Agile will help your company progressively deliver software to customers, increase customer satisfaction, and improve the level of efficiency in software development teams. Style and approach Think of this book like a manual, rather than a theoretical textbook. It’s packed full of visual ways to understand Agile, helpful tips to get you set up quickly, tried and tested solutions when challenges arise, and heaps of support to get the day-to-day tasks in Agile done. You’ll want to keep a copy on your desk, right next to your coffee cup.

Get command of your organizational Big Data using the power of data science and analytics About This Book ? A perfect companion to boost your Big Data storing, processing, analyzing skills to help you take informed business decisions ? Work with the best tools such as Apache Hadoop, R, Python, and Spark for NoSQL platforms to perform massive online analyses ? Get expert tips on statistical inference, machine learning, mathematical modeling, and data visualization for Big Data Who This Book Is For The book is intended for existing and aspiring Big Data professionals who wish to become the go-to person in their organization when it comes to Big Data architecture, analytics, and governance. While no prior knowledge of Big Data or related technologies is assumed, it will be helpful to have some programming experience. What You Will Learn ? Get a 360-degree view into the world of Big Data, data science and machine learning ? Broad range of technical and business Big Data analytics topics that caters to the interests of the technical experts as well as corporate IT executives ? Get hands-on experience with industry-standard Big Data and machine learning tools such as Hadoop, Spark, MongoDB, KDB+ and R ? Create production-grade machine learning BI Dashboards using R and R Shiny with step-by-step instructions ? Learn how to combine open-source Big Data, machine learning and BI Tools to create low-cost business analytics applications ? Understand corporate strategies for successful Big Data and data science projects ? Go beyond general-purpose analytics to develop cutting-edge Big Data applications using emerging technologies In Detail Big Data analytics relates to the strategies used by organizations to collect, organize and analyze large amounts of data to uncover valuable business insights that otherwise cannot be analyzed through traditional systems. Crafting an enterprise-scale cost-efficient Big Data and machine learning solution to uncover insights and value from your organization's data is a challenge. Today, with hundreds of new Big Data systems, machine learning packages and BI Tools, selecting the right combination of technologies is an even greater challenge. This book will help you do that. With the help of this guide, you will be able to bridge the gap between the theoretical world of technology with the practical ground reality of building corporate Big Data and data science platforms. You will get hands-on exposure to Hadoop and Spark, build machine learning dashboards using R and R Shiny, create web-based apps using NoSQL databases such as MongoDB and even learn how to write R code for neural networks. By the end of the book, you will have a very clear and concrete understanding of what Big Data analytics means, how it drives revenues for organizations, and how you can develop your own Big Data analytics solution using different tools and methods articulated in this book. Style and approach This book equips you with a knowledge of various NoSQL tools, R, Python programming, cloud platforms, and techniques so you can use them to store, analyze, and deliver meaningful insights from your data.

Discover new opportunities to empower your private cloud by making the most of the OpenStack universe About This Book ? This practical guide teaches you how to extend the core functionalities of OpenStack ? Discover OpenStack's flexibility by writing custom applications and network plugins ? Deploy a containerized environment in OpenStack through a hands-on and example-driven approach Who This Book Is For This book is for system administrators, cloud architects, and developers who have experience working with OpenStack and are ready to step up and extend its functionalities. A good knowledge of basic OpenStack components is required. In addition, familiarity with Linux boxes and a good understanding of network and virtualization jargon is required. What You Will Learn ? Explore new incubated projects in the OpenStack ecosystem and see how they work ? Architect your OpenStack private cloud with extended features of the latest versions ? Consolidate OpenStack authentication in your large infrastructure to avoid complexity ? Find out how to expand your computing power in OpenStack on a large scale ? Reduce your OpenStack storage cost management by taking advantage of external tools ? Provide easy, on-demand, cloud-ready applications to developers using OpenStack in no time ? Enter the big data world and find out how to launch elastic jobs easily in OpenStack ? Boost your extended OpenStack private cloud performance through real-world scenarios In Detail OpenStack is a very popular cloud computing platform that has enabled several organizations during the last few years to successfully implement their Infrastructure as a Service (IaaS) platforms. This book will guide you through new features of the latest OpenStack releases and how to bring them into production straightaway in an agile way. It starts by showing you how to expand your current OpenStack setup and how to approach your next OpenStack Data Center generation deployment. You will discover how to extend your storage and network capacity and also take advantage of containerization technology such as Docker and Kubernetes in OpenStack. Additionally, you'll explore the power of big data as a Service terminology implemented in OpenStack by integrating the Sahara project. This book will teach you how to build Hadoop clusters and launch jobs in a very simple way. Then you'll automate and deploy applications on top of OpenStack. You will discover how to write your own plugin in the Murano project. The final part of the book will go through best practices for security such as identity, access management, and authentication exposed by Keystone in OpenStack. By the end of this book, you will be ready to extend and customize your private cloud based on your requirements. Style and approach This guide is filled with practical scenarios on how to extend and enhance OpenStack's functionality. We will be covering various installation and configuration platforms along with a focus on plugins and extending OpenStack's core functionalities.

A practical guide filled with case studies and easy solutions to solve the most common user experience issues About This Book ? Understand and fix the pain points of a bad UX design to ensure greater customer satisfaction. ? Correct UX issues at various stages of a UX Design with the help of different methodologies for fixing bad UXs ? See best practices and established principles in UX with case studies illustrating these practices and principles Who This Book Is For This book is for anyone confronted with a poorly designed UX. It is ideal for UX professionals who want to solve problems with existing UX designs, and UX designers who want to enhance their designs or analyze and rectify where they went wrong. What You Will Learn ? Learn about ROI and metrics in UX ? Understand the importance of getting stakeholders involved ? Learn through real cases how to fix bad UX ? Identify and fix UX issues using different methodologies ? Learn how to turn insights and finding into practical UX solutions ? Learn to validate, test and measure the UX solutions implemented ? Learn about UX refactoring In Detail Have your web applications been experiencing more hits and less conversions? Are bad designs consuming your time and money? This book is the answer to these problems. With intuitive case studies, you’ll learn to simplify, fix, and enhance some common, real-world application designs. You’ll look at the common issues of simplicity, navigation, appearance, maintenance, and many more. The challenge that most UX designers face is to ensure that the UX is user-friendly. In this book, we address this with individual case studies starting with some common UX applications and then move on to complex applications. Each case study will help you understand the issues faced by a bad UX and teach you to break it down and fix these problems. As we progress, you’ll learn about the information architecture, usability testing, iteration, UX refactoring, and many other related features with the help of various case studies. You’ll also learn some interesting UX design tools with the projects covered in the book. By the end of the book, you’ll be armed with the knowledge to fix bad UX designs and to ensure great customer satisfaction for your applications. Style and approach This book takes a practical approach, with case studies, best practices, and practical solutions to bad design

Grasp the fundamental concepts of deep learning using Tensorflow in a hands-on manner About This Book ? Get a first-hand experience of the deep learning concepts and techniques with this easy-to-follow guide ? Train different types of neural networks using Tensorflow for real-world problems in language processing, computer vision, transfer learning, and more ? Designed for those who believe in the concept of 'learn by doing', this book is a perfect blend of theory and code examples Who This Book Is For This book targets data scientists and machine learning developers who wish to get started with deep learning. If you know what deep learning is but are not quite sure of how to use it, this book will help you as well. An understanding of statistics and data science concepts is required. Some familiarity with Python programming will also be beneficial. What You Will Learn ? Understand the fundamentals of deep learning and how it is different from machine learning ? Get familiarized with Tensorflow, one of the most popular libraries for advanced machine learning ? Increase the predictive power of your model using feature engineering ? Understand the basics of deep learning by solving a digit classification problem of MNIST ? Demonstrate face generation based on the CelebA database, a promising application of generative models ? Apply deep learning to other domains like language modeling, sentiment analysis, and machine translation In Detail Deep learning is a popular subset of machine learning, and it allows you to build complex models that are faster and give more accurate predictions. This book is your companion to take your first steps into the world of deep learning, with hands-on examples to boost your understanding of the topic. This book starts with a quick overview of the essential concepts of data science and machine learning which are required to get started with deep learning. It introduces you to Tensorflow, the most widely used machine learning library for training deep learning models. You will then work on your first deep learning problem by training a deep feed-forward neural network for digit classification, and move on to tackle other real-world problems in computer vision, language processing, sentiment analysis, and more. Advanced deep learning models such as generative adversarial networks and their applications are also covered in this book. By the end of this book, you will have a solid understanding of all the essential concepts in deep learning. With the help of the examples and code provided in this book, you will be equipped to train your own deep learning models with more confidence. Style and approach A step-by-step guide filled with multiple examples to help you get started with data science and deep learning.

A tutorial leading the aspiring Go developer to full mastery of Golang's distributed features. About This Book ? This book provides enough concurrency theory to give you a contextual understanding of Go concurrency ? It gives weight to synchronous and asynchronous data streams in Golang web applications ? It makes Goroutines and Channels completely familiar and natural to Go developers Who This Book Is For This book is for developers who are familiar with the Golang syntax and have a good idea of how basic Go development works. It would be advantageous if you have been through a web application product cycle, although it’s not necessary. What You Will Learn ? Gain proficiency with concurrency and parallelism in Go ? Learn how to test your application using Go's standard library ? Learn industry best practices with technologies such as REST, OpenAPI, Docker, and so on ? Design and build a distributed search engine ? Learn strategies on how to design a system for web scale In Detail Distributed Computing with Go gives developers with a good idea how basic Go development works the tools to fulfill the true potential of Golang development in a world of concurrent web and cloud applications. Nikhil starts out by setting up a professional Go development environment. Then you’ll learn the basic concepts and practices of Golang concurrent and parallel development. You’ll find out in the new few chapters how to balance resources and data with REST and standard web approaches while keeping concurrency in mind. Most Go applications these days will run in a data center or on the cloud, which is a condition upon which the next chapter depends. There, you’ll expand your skills considerably by writing a distributed document indexing system during the next two chapters. This system has to balance a large corpus of documents with considerable analytical demands. Another use case is the way in which a web application written in Go can be consciously redesigned to take distributed features into account. The chapter is rather interesting for Go developers who have to migrate existing Go applications to computationally and memory-intensive environments. The final chapter relates to the rather onerous task of testing parallel and distributed applications, something that is not usually taught in standard computer science curricula. Style and approach Distributed Computing with Go takes you through a series of carefully graded tutorials, building ever more sophisticated applications.

Learn the techniques for object recognition, 3D reconstruction, stereo imaging, and other computer vision applications using examples on different functions of OpenCV. About This Book ? Learn how to apply complex visual effects to images with OpenCV 3.x and Python ? Extract features from an image and use them to develop advanced applications ? Build algorithms to help you understand image content and perform visual searches ? Get to grips with advanced techniques in OpenCV such as machine learning, artificial neural network, 3D reconstruction, and augmented reality Who This Book Is For This book is intended for Python developers who are new to OpenCV and want to develop computer vision applications with OpenCV and Python. This book is also useful for generic software developers who want to deploy computer vision applications on the cloud. It would be helpful to have some familiarity with basic mathematical concepts such as vectors, matrices, and so on. What You Will Learn ? Detect shapes and edges from images and videos ? How to apply filters on images and videos ? Use different techniques to manipulate and improve images ? Extract and manipulate particular parts of images and videos ? Track objects or colors from videos ? Recognize specific object or faces from images and videos ? How to create Augmented Reality applications ? Apply artificial neural networks and machine learning to improve object recognition In Detail Computer vision is found everywhere in modern technology. OpenCV for Python enables us to run computer vision algorithms in real time. With the advent of powerful machines, we have more processing power to work with. Using this technology, we can seamlessly integrate our computer vision applications into the cloud. Focusing on OpenCV 3.x and Python 3.6, this book will walk you through all the building blocks needed to build amazing computer vision applications with ease. We start off by manipulating images using simple filtering and geometric transformations. We then discuss affine and projective transformations and see how we can use them to apply cool advanced manipulations to your photos like resizing them while keeping the content intact or smoothly removing undesired elements. We will then cover techniques of object tracking, body part recognition, and object recognition using advanced techniques of machine learning such as artificial neural network. 3D reconstruction and augmented reality techniques are also included. The book covers popular OpenCV libraries with the help of examples. This book is a practical tutorial that covers various examples at different levels, teaching you about the different functions of OpenCV and their actual implementation. By the end of this book, you will have acquired the skills to use OpenCV and Python to develop real-world computer vision applications. Style and approach The book is a practical tutorial that covers various examples at different levels, teaching you about the different functions of OpenCV and their actual implementation.

Transform yourself into a Kubernetes specialist in serverless applications. About This Book ? Get hands-on experience in installing, configuring, and using services such as Kubeless, Funktion, OpenWhisk, and Fission ? Learn how to launch Kubernetes both locally and in public clouds ? Explore the differences between using services such as AWS Lambda and Azure Functions and running your own Who This Book Is For If you are a DevOps engineer, cloud architect, or a stakeholder keen to learn about serverless functions in Kubernetes environments, then this book is for you. What You Will Learn ? Get a detailed analysis of serverless/Functions as a Service ? Get hands-on with installing and running tasks in Kubernetes using Minikube ? Install Kubeless locally and launch your first function. ? Launch Kubernetes in the cloud and move your applications between your local machine and your cloud cluster ? Deploy applications on Kubernetes using Apache OpenWhisk ? Explore topics such as Funktion and Fission installation on the cloud followed by launching applications ? Monitor a serverless function and master security best practices and Kubernetes use cases In Detail Kubernetes has established itself as the standard platform for container management, orchestration, and deployment. It has been adopted by companies such as Google, its original developers, and Microsoft as an integral part of their public cloud platforms, so that you can develop for Kubernetes and not worry about being locked into a single vendor. This book will initially start by introducing serverless functions. Then you will configure tools such as Minikube to run Kubernetes. Once you are up-and-running, you will install and configure Kubeless, your first step towards running Function as a Service (FaaS) on Kubernetes. Then you will gradually move towards running Fission, a framework used for managing serverless functions on Kubernetes environments. Towards the end of the book, you will also work with Kubernetes functions on public and private clouds. By the end of this book, we will have mastered using Function as a Service on Kubernetes environments. Style and approach A clear, concise, and straightforward book that will empower you work with clusters and run serverless functions effectively.

Deploy and manage VMware vSphere 6.5 components with ease. About This Book ? Simplified and to-the-point theory and practical recipes to deploy and manage vSphere 6.5 ? Discover the best ways to deploy stateless and stateful ESXi hosts and upgrade them ? Storage and network resource management ? Certificate management using VMCA ? Monitor the performance of a vSphere environment. Who This Book Is For If you are a system administrator, support professional, or anyone interested in learning how to install, configure, and manage a vSphere environment, then this book is for you. This task-oriented reference guide will also benefit consultants or infrastructure architects who design and deploy vSphere 6.5 environments. What You Will Learn ? Upgrade your existing vSphere environment or perform a fresh deployment. ? Automate the deployment and management of large sets of ESXi hosts in your vSphere Environment ? Configure and manage FC, iSCSI, and NAS storage, and get more control over how storage resources are allocated and managed ? Configure vSphere networking by deploying host-wide and data center-wide switches in your vSphere environment ? Configure high availability on a host cluster and learn how to enable the fair distribution and utilization of compute resources ? Patch and upgrade the vSphere environment ? Handle certificate request generation and renew component certificates ? Monitor performance of a vSphere environment In Detail VMware vSphere is a complete and robust virtualization product suite that helps transform data centers into simplified on-premises cloud infrastructures, providing for the automation and orchestration of workload deployment and life cycle management of the infrastructure. This book focuses on the latest release of VMware vSphere and follows a recipe-based approach, giving you hands-on instructions required to deploy and manage a vSphere environment. The book starts with the procedures involved in upgrading your existing vSphere infrastructure to vSphere 6.5, followed by deploying a new vSphere 6.5 environment. Then the book delves further into the procedures involved in managing storage and network access to the ESXi hosts and the virtual machines running on them. Moving on, the book covers high availability and fair distribution/utilization of clustered compute and storage resources. Finally, the book covers patching and upgrading the vSphere infrastructure using VUM, certificate management using VMCA, and finishes with a chapter covering the tools that can be used to monitor the performance of a vSphere infrastructure. Style and approach This book will quickly get you started with managing VMware components.

Discover Android programming and web development by understanding the concepts of Kotlin Programming About This Book ? Practical solutions to your common programming problems with Kotlin 1.1 ? Leverage the functional power of Kotlin to ease your Android application development ? Learn to use Java code in conjunction with Kotlin Who This Book Is For This book will appeal to Kotlin developers keen to find solutions for their common programming problems. Java programming knowledge would be an added advantage. What You Will Learn ? Understand the basics and object-oriented concepts of Kotlin Programming ? Explore the full potential of collection frameworks in Kotlin ? Work with SQLite databases in Android, make network calls, and fetch data over a network ? Use Kotlin's Anko library for efficient and quick Android development ? Uncover some of the best features of Kotlin: Lambdas and Delegates ? Set up web service development environments, write servlets, and build RESTful services with Kotlin ? Learn how to write unit tests, integration tests, and instrumentation/acceptance tests. In Detail The Android team has announced first-class support for Kotlin 1.1. This acts as an added boost to the language and more and more developers are now looking at Kotlin for their application development. This recipe-based book will be your guide to learning the Kotlin programming language. The recipes in this book build from simple language concepts to more complex applications of the language. After the fundamentals of the language, you will learn how to apply the object-oriented programming features of Kotlin 1.1. Programming with Lambdas will show you how to use the functional power of Kotlin. This book has recipes that will get you started with Android programming with Kotlin 1.1, providing quick solutions to common problems encountered during Android app development. You will also be taken through recipes that will teach you microservice and concurrent programming with Kotlin. Going forward, you will learn to test and secure your applications with Kotlin. Finally, this book supplies recipes that will help you migrate your Java code to Kotlin and will help ensure that it's interoperable with Java. Style and approach This book explains concepts related to Kotlin Programming using a practical approach and with the help of easy-to-follow recipes.

Get to grips with the essentials of deep learning by leveraging the power of Python About This Book ? Your one-stop solution to get started with the essentials of deep learning and neural network modeling ? Train different kinds of neural networks to tackle various problems in Natural Language Processing, computer vision, speech recognition, and more ? Covers popular Python libraries such as Tensorflow, Keras, and more, along with tips on training, deploying and optimizing your deep learning models in the best possible manner Who This Book Is For Aspiring data scientists and machine learning experts who have limited or no exposure to deep learning will find this book to be very useful. If you are looking for a resource that gets you up and running with the fundamentals of deep learning and neural networks, this book is for you. As the models in the book are trained using the popular Python-based libraries such as Tensorflow and Keras, it would be useful to have sound programming knowledge of Python. What You Will Learn ? Get to grips with the core concepts of deep learning and neural networks ? Set up deep learning library such as TensorFlow ? Fine-tune your deep learning models for NLP and Computer Vision applications ? Unify different information sources, such as images, text, and speech through deep learning ? Optimize and fine-tune your deep learning models for better performance ? Train a deep reinforcement learning model that plays a game better than humans ? Learn how to make your models get the best out of your GPU or CPU In Detail Deep Learning a trending topic in the field of Artificial Intelligence today and can be considered to be an advanced form of machine learning, which is quite tricky to master. This book will help you take your first steps in training efficient deep learning models and applying them in various practical scenarios. You will model, train, and deploy different kinds of neural networks such as Convolutional Neural Network, Recurrent Neural Network, and will see some of their applications in real-world domains including computer vision, natural language processing, speech recognition, and so on. You will build practical projects such as chatbots, implement reinforcement learning to build smart games, and develop expert systems for image captioning and processing. Popular Python library such as TensorFlow is used in this book to build the models. This book also covers solutions for different problems you might come across while training models, such as noisy datasets, small datasets, and more. This book does not assume any prior knowledge of deep learning. By the end of this book, you will have a firm understanding of the basics of deep learning and neural network modeling, along with their practical applications. Style and approach This step-by-step guide is filled with real-world practical examples and use cases to solve various deep learning problems.

Build effective regression models in R to extract valuable insights from real data About This Book ? Implement different regression analysis techniques to solve common problems in data science - from data exploration to dealing with missing values ? From Simple Linear Regression to Logistic Regression - this book covers all regression techniques and their implementation in R ? A complete guide to building effective regression models in R and interpreting results from them to make valuable predictions Who This Book Is For This book is intended for budding data scientists and data analysts who want to implement regression analysis techniques using R. If you are interested in statistics, data science, machine learning and wants to get an easy introduction to the topic, then this book is what you need! Basic understanding of statistics and math will help you to get the most out of the book. Some programming experience with R will also be helpful What You Will Learn ? Get started with the journey of data science using Simple linear regression ? Deal with interaction, collinearity and other problems using multiple linear regression ? Understand diagnostics and what to do if the assumptions fail with proper analysis ? Load your dataset, treat missing values, and plot relationships with exploratory data analysis ? Develop a perfect model keeping overfitting, under-fitting, and cross-validation into consideration ? Deal with classification problems by applying Logistic regression ? Explore other regression techniques – Decision trees, Bagging, and Boosting techniques ? Learn by getting it all in action with the help of a real world case study. In Detail Regression analysis is a statistical process which enables prediction of relationships between variables. The predictions are based on the casual effect of one variable upon another. Regression techniques for modeling and analyzing are employed on large set of data in order to reveal hidden relationship among the variables. This book will give you a rundown explaining what regression analysis is, explaining you the process from scratch. The first few chapters give an understanding of what the different types of learning are – supervised and unsupervised, how these learnings differ from each other. We then move to covering the supervised learning in details covering the various aspects of regression analysis. The outline of chapters are arranged in a way that gives a feel of all the steps covered in a data science process – loading the training dataset, handling missing values, EDA on the dataset, transformations and feature engineering, model building, assessing the model fitting and performance, and finally making predictions on unseen datasets. Each chapter starts with explaining the theoretical concepts and once the reader gets comfortable with the theory, we move to the practical examples to support the understanding. The practical examples are illustrated using R code including the different packages in R such as R Stats, Caret and so on. Each chapter is a mix of theory and practical examples. By the end of this book you will know all the concepts and pain-points related to regression analysis, and you will be able to implement your learning in your projects. Style and approach An easy-to-follow step by step guide which will help you get to grips with real world application of Regression Analysis with R

A practical guide designed to get you from basics to current state of art in computer vision systems. About This Book ? Master the different tasks associated with Computer Vision and develop your own Computer Vision applications with ease ? Leverage the power of Python, Tensorflow, Keras, and OpenCV to perform image processing, object detection, feature detection and more ? With real-world datasets and fully functional code, this book is your one-stop guide to understanding Computer Vision Who This Book Is For This book is for machine learning practitioners and deep learning enthusiasts who want to understand and implement various tasks associated with Computer Vision and image processing in the most practical manner possible. Some programming experience would be beneficial while knowing Python would be an added bonus. What You Will Learn ? Learn the basics of image manipulation with OpenCV ? Implement and visualize image filters such as smoothing, dilation, histogram equalization, and more ? Set up various libraries and platforms, such as OpenCV, Keras, and Tensorflow, in order to start using computer vision, along with appropriate datasets for each chapter, such as MSCOCO, MOT, and Fashion-MNIST ? Understand image transformation and downsampling with practical implementations. ? Explore neural networks for computer vision and convolutional neural networks using Keras ? Understand working on deep-learning-based object detection such as Faster-R-CNN, SSD, and more ? Explore deep-learning-based object tracking in action ? Understand Visual SLAM techniques such as ORB-SLAM In Detail In this book, you will find several recently proposed methods in various domains of computer vision. You will start by setting up the proper Python environment to work on practical applications. This includes setting up libraries such as OpenCV, TensorFlow, and Keras using Anaconda. Using these libraries, you'll start to understand the concepts of image transformation and filtering. You will find a detailed explanation of feature detectors such as FAST and ORB; you'll use them to find similar-looking objects. With an introduction to convolutional neural nets, you will learn how to build a deep neural net using Keras and how to use it to classify the Fashion-MNIST dataset. With regard to object detection, you will learn the implementation of a simple face detector as well as the workings of complex deep-learning-based object detectors such as Faster R-CNN and SSD using TensorFlow. You'll get started with semantic segmentation using FCN models and track objects with Deep SORT. Not only this, you will also use Visual SLAM techniques such as ORB-SLAM on a standard dataset. By the end of this book, you will have a firm understanding of the different computer vision techniques and how to apply them in your applications. Style and approach Step-by-step guide filled with real-world, practical examples for understanding and applying various Computer Vision techniques

Become an Ethereum Blockchain developer using a blend of concepts and hands-on implementations About This Book ? Understand the Ethereum Ecosystem and its differences from its rich cousin Bitcoin ? Explore the Solidity programming language and smart contract optimizations ? Get a developer’s perspective of Blockchain-as-a-technology with exposure to common challenges faced while building decentralized applications Who This Book Is For If you want to know the ins and outs of the Ethereum network and build your own decentralized applications, then this book is what you need! This book is for anyone who is interested in blockchain and wants to become an Ethereum developer. It’s ideal for existing Ethereum developers who want to develop Ethereum using smart contracts. Basic knowledge of cryptography is expected but is not mandatory. What You Will Learn ? Know how to build your own smart contracts and cryptocurrencies ? Understand the Solidity language ? Find out about data types, control structure, functions, inheritance, mathematical operations, and much more ? See the various types of forks and discover how they are related to Ethereum ? Get to know the various concepts of web3.js and its APIs so you can build client-side apps ? Build a DAO from scratch and acquire basic knowledge of DApps on Ethercast ? Be guided through the project so you can optimize EVM for smart contracts ? Build your own decentralized applications (DApps) by taking a practical approach In Detail Ethereum is a public, blockchain-based distributed computing platform featuring smart contract functionality. This book is your one-stop guide to blockchain and Ethereum smart contract development. We start by introducing you to the basics of blockchain. You'll learn about hash functions, Merkle trees, forking, mining, and much more. Then you'll learn about Ethereum and smart contracts, and we'll cover Ethereum virtual machine (EVM) in detail. Next, you'll get acquainted with DApps and DAOs and see how they work. We'll also delve into the mechanisms of advanced smart contracts, taking a practical approach. You'll also learn how to develop your own cryptocurrency from scratch in order to understand the business behind ICO. Further on, you'll get to know the key concepts of the Solidity programming language, enabling you to build decentralized blockchain-based applications. We'll also look at enterprise use cases, where you'll build a decentralized microblogging site. At the end of this book, we discuss blockchain-as-a-service, the dark web marketplace, and various advanced topics so you can get well versed with the blockchain principles and ecosystem. Style and approach This comprehensive guide takes a practical approach by showing you how to implement Blockchain in different Enterprise use cases. You’ll quickly brush up on the basics of the blockchain database, then learn the advanced intricacies of smart contract development.

Gain comprehensive insight into WPF mechanics and capabilities. About This Book ? Gain a strong foundation in WPF features and patterns ? Leverage the MVVM pattern to build decoupled, maintainable apps ? Increase efficiency through Performance tuning and UI automation Who This Book Is For The book is intended for developers who are relatively new to WPF (Windows Presentation Foundation), or those who have been working with WPF for some time, but want to get a deeper understanding of its foundation and concepts to gain practical knowledge. Basic knowledge of C# and Visual Studio is assumed. What You Will Learn ? Understand the fundamentals of WPF ? Explore the major controls and manage element layout ? Implement data binding ? Create custom elements that lead to a particular implementation path ? Customize controls, styles, and templates in XAML ? Leverage the MVVM pattern to maintain a clean and reusable structure in your code ? Master practical animations ? Integrate WCF services in a WPF application ? Implement WPFs support for debugging and asynchronous operations In Detail Windows Presentation Foundation (WPF) is Microsoft's development tool for building rich Windows client user experiences that incorporate UIs, media, and documents. With the updates in .NET 4.7, Visual Studio 2017, C# 7, and .NET Standard 2.0, WPF has taken giant strides and is now easier than ever for developers to use. If you want to get an in-depth view of WPF mechanics and capabilities, then this book is for you. The book begins by teaching you about the fundamentals of WPF and then quickly shows you the standard controls and the layout options. It teaches you about data bindings and how to utilize resources and the MVVM pattern to maintain a clean and reusable structure in your code. After this, you will explore the animation capabilities of WPF and see how they integrate with other mechanisms. Towards the end of the book, you will learn about WCF services and explore WPF's support for debugging and asynchronous operations. By the end of the book, you will have a deep understanding of WPF and will know how to build resilient applications. Style and approach This book takes a recipe-based approach to teaching you how to create fault-tolerant WPF applications.

Build your own hybrid cloud strategy with this comprehensive learning guide. About This Book ? Build a hybrid cloud strategy for your organization with AWS and OpenStack ? Leverage Hybrid Cloud to design a complex deployment pipeline ? Learn to implement security and monitoring best practices with real-world examples Who This Book Is For This book is targeted at cloud architects, cloud solution providers, DevOps engineers, or any working stakeholder who wants to learn about the hybrid cloud architecture. A basic understanding of public and private cloud is desirable. What You Will Learn ? Learn the demographics and definitions of Hybrid Cloud ? Understand the different architecture and design of Hybrid Cloud ? Explore multi-cloud strategy and use it with your hybrid cloud ? Implement a Hybrid Cloud using CMP / Common API’s ? Implement a Hybrid Cloud using Containers ? Overcome various challenges and issues while working with your Hybrid Cloud ? Understand how to monitor your Hybrid Cloud ? Discover the security implications in the Hybrid Cloud In Detail Hybrid cloud is currently the buzz word in the cloud world. Organizations are planning to adopt hybrid cloud strategy due to its advantages such as untested workloads, cloud-bursting, cloud service brokering and so on. This book will help you understand the dynamics, design principles, and deployment strategies of a Hybrid Cloud. You will start by understanding the concepts of hybrid cloud and the problems it solves as compared to a stand-alone public and private cloud. You will be delving into the different architecture and design of hybrid cloud. The book will then cover advanced concepts such as building a deployment pipeline, containerization strategy, and data storage mechanism. Next up, you will be able to deploy an external CMP to run a Hybrid cloud and integrate it with your OpenStack and AWS environments. You will also understand the strategy for designing a Hybrid Cloud using containerization and work with pre-built solutions like vCloud Air, VMware for AWS, and Azure Stack. Finally, the book will cover security and monitoring related best practices that will help you secure your cloud infrastructure. By the end of the book, you will be in a position to build a hybrid cloud strategy for your organization. Style and approach This book follows a step-by-step, practical approach to deploying and implementing hybrid cloud architectures using AWS and OpenStack.

Build neural network models in text, vision and advanced analytics using PyTorch About This Book ? Learn PyTorch for implementing cutting-edge deep learning algorithms. ? Train your neural networks for higher speed and flexibility and learn how to implement them in various scenarios; ? Cover various advanced neural network architecture such as ResNet, Inception, DenseNet and more with practical examples; Who This Book Is For This book is for machine learning engineers, data analysts, data scientists interested in deep learning and are looking to explore implementing advanced algorithms in PyTorch. Some knowledge of machine learning is helpful but not a mandatory need. Working knowledge of Python programming is expected. What You Will Learn ? Use PyTorch for GPU-accelerated tensor computations ? Build custom datasets and data loaders for images and test the models using torchvision and torchtext ? Build an image classifier by implementing CNN architectures using PyTorch ? Build systems that do text classification and language modeling using RNN, LSTM, and GRU ? Learn advanced CNN architectures such as ResNet, Inception, Densenet, and learn how to use them for transfer learning ? Learn how to mix multiple models for a powerful ensemble model ? Generate new images using GAN’s and generate artistic images using style transfer In Detail Deep learning powers the most intelligent systems in the world, such as Google Voice, Siri, and Alexa. Advancements in powerful hardware, such as GPUs, software frameworks such as PyTorch, Keras, Tensorflow, and CNTK along with the availability of big data have made it easier to implement solutions to problems in the areas of text, vision, and advanced analytics. This book will get you up and running with one of the most cutting-edge deep learning libraries—PyTorch. PyTorch is grabbing the attention of deep learning researchers and data science professionals due to its accessibility, efficiency and being more native to Python way of development. You'll start off by installing PyTorch, then quickly move on to learn various fundamental blocks that power modern deep learning. You will also learn how to use CNN, RNN, LSTM and other networks to solve real-world problems. This book explains the concepts of various state-of-the-art deep learning architectures, such as ResNet, DenseNet, Inception, and Seq2Seq, without diving deep into the math behind them. You will also learn about GPU computing during the course of the book. You will see how to train a model with PyTorch and dive into complex neural networks such as generative networks for producing text and images. By the end of the book, you'll be able to implement deep learning applications in PyTorch with ease. Style and approach An end-to-end guide that teaches you all about PyTorch and how to implement it in various scenarios.

Leverage the WiFi chip to build exciting Quadcopters About This Book ? Learn to create a fully functional Drone with Arduino and ESP8266 and their modified versions of hardware. ? Enhance your drone's functionalities by implementing smart features. ? A project-based guide that will get you developing next-level drones to help you monitor a particular area with mobile-like devices. Who This Book Is For If you are a programmer or a DIY enthusiast and keen to create a fully functional drone with Arduino and ESP8266, then this book is for you. Basic skills in electronics and programming would be beneficial. This book is not for the beginners as it includes lots of ideas not detailed how you can do that. If you are a beginner, then you might get lost here. The prerequisites of the book include a good knowledge of Arduino, electronics, programming in C or C++ and lots of interest in creating things out of nothing. What You Will Learn ? Includes a number of projects that utilize different ESP8266 and Arduino capabilities, while interfacing with external hardware ? Covers electrical engineering and programming concepts, interfacing with the World through analog and digital sensors, communicating with a computer and other devices, and internet connectivity ? Control and fly your quadcopter, taking into account weather conditions ? Build a drone that can follow the user wherever he/she goes ? Build a mission-control drone and learn how to use it effectively ? Maintain your vehicle as much as possible and repair it whenever required In Detail With the use of drones, DIY projects have taken off. Programmers are rapidly moving from traditional application programming to developing exciting multi-utility projects. This book will teach you to build industry-level drones with Arduino and ESP8266 and their modified versions of hardware. With this book, you will explore techniques for leveraging the tiny WiFi chip to enhance your drone and control it over a mobile phone. This book will start with teaching you how to solve problems while building your own WiFi controlled Arduino based drone. You will also learn how to build a Quadcopter and a mission critical drone. Moving on you will learn how to build a prototype drone that will be given a mission to complete which it will do it itself. You will also learn to build various exciting projects such as gliding and racing drones. By the end of this book you will learn how to maintain and troubleshoot your drone. By the end of this book, you will have learned to build drones using ESP8266 and Arduino and leverage their functionalities to the fullest. Style and approach This is an easy-to-follow guide with illustrations and technical de*ions to help you assemble your vehicle.

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