Leverage this step-by-step guide to build a highly secure, fault-tolerant, and scalable Cloud environment About This Book ? Learn how to leverage various Amazon Web Services (AWS) components and services to build a secure, reliable, and robust environment to host your applications on. ? Delve into core AWS service offerings with hands-on tutorials, real-world use case scenarios, and best practices. ? A self-paced, systematic, and step-by-step guide to learning and implementing AWS in your own environment. Who This Book Is For This book is for those who want to learn and leverage the rich plethora of services provided by AWS. Although no prior experience with AWS is required, it is recommended that you have some hands-on experience of Linux, Web Services, and basic networking. What You Will Learn ? Take an in-depth look at what's new with AWS, along with how to effectively manage and automate your EC2 infrastructure with AWS Systems Manager ? Deploy and scale your applications with ease using AWS Elastic Beanstalk and Amazon Elastic File System ? Secure and govern your environments using AWS CloudTrail, AWS Config, and AWS Shield ? Learn the DevOps way using a combination of AWS CodeCommit, AWS CodeDeploy, and AWS CodePipeline ? Run big data analytics and workloads using Amazon EMR and Amazon Redshift ? Learn to back up and safeguard your data using AWS Data Pipeline ? Get started with the Internet of Things using AWS IoT and AWS Greengrass In Detail Many businesses are moving from traditional data centers to AWS because of its reliability, vast service offerings, lower costs, and high rate of innovation. AWS can be used to accomplish a variety of both simple and tedious tasks. Whether you are a seasoned system admin or a rookie, this book will help you to learn all the skills you need to work with the AWS cloud. This book guides you through some of the most popular AWS services, such as EC2, Elastic Beanstalk, EFS, CloudTrail, Redshift, EMR, Data Pipeline, and IoT using a simple, real-world, application-hosting example. This book will also enhance your application delivery skills with the latest AWS services, such as CodeCommit, CodeDeploy, and CodePipeline, to provide continuous delivery and deployment, while also securing and monitoring your environment's workflow. Each chapter is designed to provide you with maximal information about each AWS service, coupled with easy to follow, hands-on steps, best practices, tips, and recommendations. By the end of the book, you will be able to create a highly secure, fault-tolerant, and scalable environment for your applications to run on. Style and approach This in-depth and insightful guide is filled with easy-to-follow examples, real-world use cases, best practices, and recommendations that will help you design and leverage some of the most commonly used AWS services.

Leverage the power of Python to build DIY robotic projects About This Book ? Design, build, and stimulate collaborative robots ? Build high-end robotics projects such as a customized personal Jarvis ? Leverage the power of Python and ROS for DIY robotic projects Who This Book Is For If building robots is your dream, then this book is made for you. Prior knowledge of Python would be an added advantage. What You Will Learn ? Get to know the basics of robotics and its functions ? Walk through interface components with microcontrollers ? Integrate robotics with the IoT environment ? Build projects using machine learning ? Implement path planning and vision processing ? Interface your robots with Bluetooth In Detail Robotics is a fast-growing industry. Multiple surveys state that investment in the field has increased tenfold in the last 6 years, and is set to become a $100-billion sector by 2020. Robots are prevalent throughout all industries, and they are all set to be a part of our domestic lives. This book starts with the installation and basic steps in configuring a robotic controller. You'll then move on to setting up your environment to use Python with the robotic controller. You'll dive deep into building simple robotic projects, such as a pet-feeding robot, and more complicated projects, such as machine learning enabled home automation system (Jarvis), vision processing based robots and a self-driven robotic vehicle using Python. By the end of this book, you'll know how to build smart robots using Python. Style and approach A simple step-by-step guide to help you learn the concepts of robotics using simple to advanced steps. You’ll not only learn the concepts of AI, machine learning, and Vision Processing, but also how to practically implement them in your projects.

A definitive guide to creating an intelligent web application with the best of machine learning and JavaScript About This Book ? Solve complex computational problems in browser with JavaScript ? Teach your browser how to learn from rules using the power of machine learning ? Understand discoveries on web interface and API in machine learning Who This Book Is For This book is for you if you are a JavaScript developer who wants to implement machine learning to make applications smarter, gain insightful information from the data, and enter the field of machine learning without switching to another language. Working knowledge of JavaScript language is expected to get the most out of the book. What You Will Learn ? Get an overview of state-of-the-art machine learning ? Understand the pre-processing of data handling, cleaning, and preparation ? Learn Mining and Pattern Extraction with JavaScript ? Build your own model for classification, clustering, and prediction ? Identify the most appropriate model for each type of problem ? Apply machine learning techniques to real-world applications ? Learn how JavaScript can be a powerful language for machine learning In Detail In over 20 years of existence, JavaScript has been pushing beyond the boundaries of web evolution with proven existence on servers, embedded devices, Smart TVs, IoT, Smart Cars, and more. Today, with the added advantage of machine learning research and support for JS libraries, JavaScript makes your browsers smarter than ever with the ability to learn patterns and reproduce them to become a part of innovative products and applications. Hands-on Machine Learning with JavaScript presents various avenues of machine learning in a practical and objective way, and helps implement them using the JavaScript language. Predicting behaviors, analyzing feelings, grouping data, and building neural models are some of the skills you will build from this book. You will learn how to train your machine learning models and work with different kinds of data. During this journey, you will come across use cases such as face detection, spam filtering, recommendation systems, character recognition, and more. Moreover, you will learn how to work with deep neural networks and guide your applications to gain insights from data. By the end of this book, you'll have gained hands-on knowledge on evaluating and implementing the right model, along with choosing from different JS libraries, such as NaturalNode, brain, harthur, classifier, and many more to design smarter applications. Style and approach This is a practical tutorial that uses hands-on examples to step through some real-world applications of machine learning. Without shying away from the technical details, you will explore machine learning with JavaScript using clear and practical examples.

Master the art of implementing scalable and reactive microservices in your production environment with Java 11 Key Features * Use domain-driven designs to build microservices * Explore various microservices design patterns such as service discovery, registration, and API Gateway * Use Kafka, Avro, and Spring Streams to implement event-based microservices Book Description Microservices are key to designing scalable, easy-to-maintain applications. This latest edition of Mastering Microservices with Java, works on Java 11. It covers a wide range of exciting new developments in the world of microservices, including microservices patterns, interprocess communication with gRPC, and service orchestration. This book will help you understand how to implement microservice-based systems from scratch. You'll start off by understanding the core concepts and framework, before focusing on the high-level design of large software projects. You'll then use Spring Security to secure microservices and test them effectively using REST Java clients and other tools. You will also gain experience of using the Netflix OSS suite, comprising the API Gateway, service discovery and registration, and Circuit Breaker. Additionally, you'll be introduced to the best patterns, practices, and common principles of microservice design that will help you to understand how to troubleshoot and debug the issues faced during development. By the end of this book, you'll have learned how to build smaller, lighter, and faster services that can be implemented easily in a production environment. What you will learn * Use domain-driven designs to develop and implement microservices * Understand how to implement microservices using Spring Boot * Explore service orchestration and distributed transactions using the Sagas * Discover interprocess communication using REpresentational State Transfer (REST) and events * Gain knowledge of how to implement and design reactive microservices * Deploy and test various microservices Who this book is for This book is designed for Java developers who are familiar with microservices architecture and now want to effectively implement microservices at an enterprise level. Basic knowledge and understanding of core microservice elements and applications is necessary.

Discover Golang's GUI libraries such as Go-GTK (GIMP Toolkit) and Go-Qt and build beautiful, performant, and responsive graphical applications Key Features * Conceptualize and build state-of-art GUI applications with Golang (Go) * Tackle the complexity of varying GUI application sizes with a structured and scalable approach * Get hands-on experience of GUI development with Shiny, and labs/ui, Fyne, and Walk Book Description Go is often compared to C++ when it comes to low-level programming and implementations that require faster processing, such as Graphical User Interfaces (GUIs). In fact, many claim that Go is superior to C++ in terms of its concurrency and ease of use. Most graphical application toolkits, though, are still written using C or C++, and so they don't enjoy the benefits of using a modern programming language such as Go. This guide to programming GUIs with Go 1.11 explores the various toolkits available, including UI, Walk, Shiny, and Fyne. The book compares the vision behind each project to help you pick the right approach for your project. Each framework is described in detail, outlining how you can build performant applications that users will love. To aid you further in creating applications using these emerging technologies, you'll be able to easily refer to code samples and screenshots featured in the book. In addition to toolkit-specific discussions, you'll cover more complex topics, such as how to structure growing graphical applications, and how cross-platform applications can integrate with each desktop operating system to create a seamless user experience. By delving into techniques and best practices for organizing and scaling Go-based graphical applications, you'll also glimpse Go's impressive concurrency system. In the concluding chapters, you'll discover how to distribute to the main desktop marketplaces and distribution channels. By the end of this book, you'll be a confident GUI developer who can use the Go language to boost the performance of your applications. What you will learn * Understand the benefits and complexities of building native graphical applications * Gain insights into how Go makes cross-platform graphical application development simple * Build platform-native GUI applications using andlabs/ui * Develop graphical Windows applications using Walk * Create multiplatform GUI applications using Shiny, Nuklear, and Fyne * Use Go wrappers for GTK and Qt for GUI application development * Streamline your requirements to pick the correct toolkit strategy Who this book is for This book is designed for Go developers who are interested in building native graphical applications for desktop computers and beyond. Some knowledge of building applications using Go is useful, but not essential. Experience in developing GUIs is not required as the book explores the benefits and challenges they pose. This book will also be beneficial for GUI application developers who are interested in trying Go.

Discover the latest features of Spring framework by building robust, fast, and reactive web applications Key Features * Take advantage of all the features of Spring 5.0 with third party tools to build a robust back end * Secure Spring based web application using Spring Security framework with LDAP and OAuth protocol * Develop robust and scalable microservice based applications on Spring Cloud, using Spring Boot Book Description Spring makes it easy to create RESTful applications, merge with social services, communicate with modern databases, secure your system, and make your code modular and easy to test. With the arrival of Spring Boot, developers can really focus on the code and deliver great value, with minimal contour. This book will show you how to build various projects in Spring 5.0, using its features and third party tools. We'll start by creating a web application using Spring MVC, Spring Data, the World Bank API for some statistics on different countries, and MySQL database. Moving ahead, you'll build a RESTful web services application using Spring WebFlux framework. You'll be then taken through creating a Spring Boot-based simple blog management system, which uses Elasticsearch as the data store. Then, you'll use Spring Security with the LDAP libraries for authenticating users and create a central authentication and authorization server using OAuth 2 protocol. Further, you'll understand how to create Spring Boot-based monolithic application using JHipster. Toward the end, we'll create an online book store with microservice architecture using Spring Cloud and Net?ix OSS components, and a task management system using Spring and Kotlin. By the end of the book, you'll be able to create coherent and ?exible real-time web applications using Spring Framework. What you will learn * Build Spring based application using Bootstrap template and JQuery * Understand the Spring WebFlux framework and how it uses Reactor library * Interact with Elasticsearch for indexing, querying, and aggregating data * Create a simple monolithic application using JHipster * Use Spring Security and Spring Security LDAP and OAuth libraries for Authentication * Develop a microservice-based application with Spring Cloud and Netflix * Work on Spring Framework with Kotlin Who this book is for This book is for competent Spring developers who wish to understand how to develop complex yet flexible applications with Spring. You must have a good knowledge of Java programming and be familiar with the basics of Spring.

Discover a project-based approach to mastering machine learning concepts by applying them to everyday problems using libraries such as scikit-learn, TensorFlow, and Keras Key Features * Get to grips with Python's machine learning libraries including scikit-learn, TensorFlow, and Keras * Implement advanced concepts and popular machine learning algorithms in real-world projects * Build analytics, computer vision, and neural network projects Book Description Machine learning is transforming the way we understand and interact with the world around us. This book is the perfect guide for you to put your knowledge and skills into practice and use the Python ecosystem to cover key domains in machine learning. This second edition covers a range of libraries from the Python ecosystem, including TensorFlow and Keras, to help you implement real-world machine learning projects. The book begins by giving you an overview of machine learning with Python. With the help of complex datasets and optimized techniques, you’ll go on to understand how to apply advanced concepts and popular machine learning algorithms to real-world projects. Next, you’ll cover projects from domains such as predictive analytics to analyze the stock market and recommendation systems for GitHub repositories. In addition to this, you’ll also work on projects from the NLP domain to create a custom news feed using frameworks such as scikit-learn, TensorFlow, and Keras. Following this, you’ll learn how to build an advanced chatbot, and scale things up using PySpark. In the concluding chapters, you can look forward to exciting insights into deep learning and you'll even create an application using computer vision and neural networks. By the end of this book, you’ll be able to analyze data seamlessly and make a powerful impact through your projects. What you will learn * Understand the Python data science stack and commonly used algorithms * Build a model to forecast the performance of an Initial Public Offering (IPO) over an initial discrete trading window * Understand NLP concepts by creating a custom news feed * Create applications that will recommend GitHub repositories based on ones you’ve starred, watched, or forked * Gain the skills to build a chatbot from scratch using PySpark * Develop a market-prediction app using stock data * Delve into advanced concepts such as computer vision, neural networks, and deep learning Who this book is for This book is for machine learning practitioners, data scientists, and deep learning enthusiasts who want to take their machine learning skills to the next level by building real-world projects. The intermediate-level guide will help you to implement libraries from the Python ecosystem to build a variety of projects addressing various machine learning domains. Knowledge of Python programming and machine learning concepts will be helpful.

Bayesian modeling with PyMC3 and exploratory analysis of Bayesian models with ArviZ Key Features *A step-by-step guide to conduct Bayesian data analyses using PyMC3 and ArviZ *A modern, practical and computational approach to Bayesian statistical modeling *A tutorial for Bayesian analysis and best practices with the help of sample problems and practice exercises. Book Description The second edition of Bayesian Analysis with Python is an introduction to the main concepts of applied Bayesian inference and its practical implementation in Python using PyMC3, a state-of-the-art probabilistic programming library, and ArviZ, a new library for exploratory analysis of Bayesian models. The main concepts of Bayesian statistics are covered using a practical and computational approach. Synthetic and real data sets are used to introduce several types of models, such as generalized linear models for regression and classification, mixture models, hierarchical models, and Gaussian processes, among others. By the end of the book, you will have a working knowledge of probabilistic modeling and you will be able to design and implement Bayesian models for your own data science problems. After reading the book you will be better prepared to delve into more advanced material or specialized statistical modeling if you need to. What you will learn *Build probabilistic models using the Python library PyMC3 *Analyze probabilistic models with the help of ArviZ *Acquire the skills required to sanity check models and modify them if necessary *Understand the advantages and caveats of hierarchical models *Find out how different models can be used to answer different data analysis questions *Compare models and choose between alternative ones *Discover how different models are unified from a probabilistic perspective *Think probabilistically and benefit from the flexibility of the Bayesian framework Who this book is for If you are a student, data scientist, researcher, or a developer looking to get started with Bayesian data analysis and probabilistic programming, this book is for you. The book is introductory so no previous statistical knowledge is required, although some experience in using Python and NumPy is expected.

Explore effective trading strategies in real-world markets using NumPy, spaCy, pandas, scikit-learn, and Keras Key Features *Implement machine learning algorithms to build, train, and validate algorithmic models *Create your own algorithmic design process to apply probabilistic machine learning approaches to trading decisions *Develop neural networks for algorithmic trading to perform time series forecasting and smart analytics Book Description The explosive growth of digital data has boosted the demand for expertise in trading strategies that use machine learning (ML). This book enables you to use a broad range of supervised and unsupervised algorithms to extract signals from a wide variety of data sources and create powerful investment strategies. This book shows how to access market, fundamental, and alternative data via API or web scraping and offers a framework to evaluate alternative data. You’ll practice the ML work?ow from model design, loss metric definition, and parameter tuning to performance evaluation in a time series context. You will understand ML algorithms such as Bayesian and ensemble methods and manifold learning, and will know how to train and tune these models using pandas, statsmodels, sklearn, PyMC3, xgboost, lightgbm, and catboost. This book also teaches you how to extract features from text data using spaCy, classify news and assign sentiment scores, and to use gensim to model topics and learn word embeddings from financial reports. You will also build and evaluate neural networks, including RNNs and CNNs, using Keras and PyTorch to exploit unstructured data for sophisticated strategies. Finally, you will apply transfer learning to satellite images to predict economic activity and use reinforcement learning to build agents that learn to trade in the OpenAI Gym. What you will learn *Implement machine learning techniques to solve investment and trading problems *Leverage market, fundamental, and alternative data to research alpha factors *Design and fine-tune supervised, unsupervised, and reinforcement learning models *Optimize portfolio risk and performance using pandas, NumPy, and scikit-learn *Integrate machine learning models into a live trading strategy on Quantopian *Evaluate strategies using reliable backtesting methodologies for time series *Design and evaluate deep neural networks using Keras, PyTorch, and TensorFlow *Work with reinforcement learning for trading strategies in the OpenAI Gym Who this book is for Hands-On Machine Learning for Algorithmic Trading is for data analysts, data scientists, and Python developers, as well as investment analysts and portfolio managers working within the finance and investment industry. If you want to perform efficient algorithmic trading by developing smart investigating strategies using machine learning algorithms, this is the book for you. Some understanding of Python and machine learning techniques is mandatory.

Create advanced applications with Python and OpenCV, exploring the potential of facial recognition, machine learning, deep learning, web computing and augmented reality. Key Features * Develop your computer vision skills by mastering algorithms in Open Source Computer Vision 4 (OpenCV 4)and Python * Apply machine learning and deep learning techniques with TensorFlow, Keras, and PyTorch * Discover the modern design patterns you should avoid when developing efficient computer vision applications Book Description OpenCV is considered to be one of the best open source computer vision and machine learning software libraries. It helps developers build complete projects in relation to image processing, motion detection, or image segmentation, among many others. OpenCV for Python enables you to run computer vision algorithms smoothly in real time, combining the best of the OpenCV C++ API and the Python language. In this book, you'll get started by setting up OpenCV and delving into the key concepts of computer vision. You'll then proceed to study more advanced concepts and discover the full potential of OpenCV. The book will also introduce you to the creation of advanced applications using Python and OpenCV, enabling you to develop applications that include facial recognition, target tracking, or augmented reality. Next, you'll learn machine learning techniques and concepts, understand how to apply them in real-world examples, and also explore their benefits, including real-time data production and faster data processing. You'll also discover how to translate the functionality provided by OpenCV into optimized application code projects using Python bindings. Toward the concluding chapters, you'll explore the application of artificial intelligence and deep learning techniques using the popular Python libraries TensorFlow, and Keras. By the end of this book, you'll be able to develop advanced computer vision applications to meet your customers' demands. What you will learn * Handle files and images, and explore various image processing techniques * Explore image transformations, including translation, resizing, and cropping * Gain insights into building histograms * Brush up on contour detection, filtering, and drawing * Work with Augmented Reality to build marker-based and markerless applications * Work with the main machine learning algorithms in OpenCV * Explore the deep learning Python libraries and OpenCV deep learning capabilities * Create computer vision and deep learning web applications Who this book is for This book is designed for computer vision developers, engineers, and researchers who want to develop modern computer vision applications. Basic experience of OpenCV and Python programming is a must.

Test, fuzz, and break web applications and services using Burp Suite’s powerful capabilities Key Features * Master the skills to perform various types of security tests on your web applications * Get hands-on experience working with components like scanner, proxy, intruder and much more * Discover the best-way to penetrate and test web applications Book Description Burp suite is a set of graphic tools focused towards penetration testing of web applications. Burp suite is widely used for web penetration testing by many security professionals for performing different web-level security tasks. The book starts by setting up the environment to begin an application penetration test. You will be able to configure the client and apply target whitelisting. You will also learn to setup and configure Android and IOS devices to work with Burp Suite. The book will explain how various features of Burp Suite can be used to detect various vulnerabilities as part of an application penetration test. Once detection is completed and the vulnerability is confirmed, you will be able to exploit a detected vulnerability using Burp Suite. The book will also covers advanced concepts like writing extensions and macros for Burp suite. Finally, you will discover various steps that are taken to identify the target, discover weaknesses in the authentication mechanism, and finally break the authentication implementation to gain access to the administrative console of the application. By the end of this book, you will be able to effectively perform end-to-end penetration testing with Burp Suite. What you will learn * Set up Burp Suite and its configurations for an application penetration test * Proxy application traffic from browsers and mobile devices to the server * Discover and identify application security issues in various scenarios * Exploit discovered vulnerabilities to execute commands * Exploit discovered vulnerabilities to gain access to data in various datastores * Write your own Burp Suite plugin and explore the Infiltrator module * Write macros to automate tasks in Burp Suite Who this book is for If you are interested in learning how to test web applications and the web part of mobile applications using Burp, then this is the book for you. It is specifically designed to meet your needs if you have basic experience in using Burp and are now aiming to become a professional Burp user.

Speed up the design and implementation of deep learning solutions using Apache Spark Key Features * Explore the world of distributed deep learning with Apache Spark * Train neural networks with deep learning libraries such as BigDL and TensorFlow * Develop Spark deep learning applications to intelligently handle large and complex datasets Book Description Deep learning is a subset of machine learning where datasets with several layers of complexity can be processed. Hands-On Deep Learning with Apache Spark addresses the sheer complexity of technical and analytical parts and the speed at which deep learning solutions can be implemented on Apache Spark. The book starts with the fundamentals of Apache Spark and deep learning. You will set up Spark for deep learning, learn principles of distributed modeling, and understand different types of neural nets. You will then implement deep learning models, such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and long short-term memory (LSTM) on Spark. As you progress through the book, you will gain hands-on experience of what it takes to understand the complex datasets you are dealing with. During the course of this book, you will use popular deep learning frameworks, such as TensorFlow, Deeplearning4j, and Keras to train your distributed models. By the end of this book, you'll have gained experience with the implementation of your models on a variety of use cases. What you will learn * Understand the basics of deep learning * Set up Apache Spark for deep learning * Understand the principles of distribution modeling and different types of neural networks * Obtain an understanding of deep learning algorithms * Discover textual analysis and deep learning with Spark * Use popular deep learning frameworks, such as Deeplearning4j, TensorFlow, and Keras * Explore popular deep learning algorithms Who this book is for If you are a Scala developer, data scientist, or data analyst who wants to learn how to use Spark for implementing efficient deep learning models, Hands-On Deep Learning with Apache Spark is for you. Knowledge of the core machine learning concepts and some exposure to Spark will be helpful.

Create clean code with Dependency Injection principles About This Book ? Use DI to make your code loosely coupled to manage and test your applications easily on Spring 5 and Google Guice ? Learn the best practices and methodologies to implement DI ? Write more maintainable Java code by decoupling your objects from their implementations Who This Book Is For This book is for Java developers who would like to implement DI in their application. Prior knowledge of the Spring and Guice frameworks and Java programming is assumed. What You Will Learn ? Understand the benefits of DI and fo from a tightly coupled design to a cleaner design organized around dependencies ? See Java 9’s new features and modular framework ? Set up Guice and Spring in an application so that it can be used for DI ? Write integration tests for DI applications ? Use scopes to handle complex application scenarios ? Integrate any third-party library in your DI-enabled application ? Implement Aspect-Oriented Programming to handle common cross-cutting concerns such as logging, authentication, and transactions ? Understand IoC patterns and anti-patterns in DI In Detail Dependency Injection (DI) is a design pattern that allows us to remove the hard-coded dependencies and make our application loosely coupled, extendable, and maintainable. We can implement DI to move the dependency resolution from compile-time to runtime. This book will be your one stop guide to write loosely coupled code using the latest features of Java 9 with frameworks such as Spring 5 and Google Guice. We begin by explaining what DI is and teaching you about IoC containers. Then you’ll learn about object compositions and their role in DI. You’ll find out how to build a modular application and learn how to use DI to focus your efforts on the business logic unique to your application and let the framework handle the infrastructure work to put it all together. Moving on, you’ll gain knowledge of Java 9’s new features and modular framework and how DI works in Java 9. Next, we’ll explore Spring and Guice, the popular frameworks for DI. You’ll see how to define injection keys and configure them at the framework-specific level. After that, you’ll find out about the different types of scopes available in both popular frameworks. You’ll see how to manage dependency of cross-cutting concerns while writing applications through aspect-oriented programming. Towards the end, you’ll learn to integrate any third-party library in your DI-enabled application and explore common pitfalls and recommendations to build a solid application with the help of best practices, patterns, and anti-patterns in DI. Style and approach This book will take an easy-to-understand, step-by-step approach providing hands-on examples at every stage.

Exploit design, deployment, and management of large-scale containers About This Book ? Explore the latest features available in Kubernetes 1.10 ? Ensure that your clusters are always available, scalable, and up to date ? Master the skills of designing and deploying large clusters on various cloud platforms Who This Book Is For Mastering Kubernetes is for you if you are a system administrator or a developer who has an intermediate understanding of Kubernetes and wish to master its advanced features. Basic knowledge of networking would also be helpful. In all, this advanced-level book provides a smooth pathway to mastering Kubernetes. What You Will Learn ? Architect a robust Kubernetes cluster for long-time operation ? Discover the advantages of running Kubernetes on GCE, AWS, Azure, and bare metal ? Understand the identity model of Kubernetes, along with the options for cluster federation ? Monitor and troubleshoot Kubernetes clusters and run a highly available Kubernetes ? Create and configure custom Kubernetes resources and use third-party resources in your automation workflows ? Enjoy the art of running complex stateful applications in your container environment ? Deliver applications as standard packages In Detail Kubernetes is an open source system that is used to automate the deployment, scaling, and management of containerized applications. If you are running more containers or want automated management of your containers, you need Kubernetes at your disposal. To put things into perspective, Mastering Kubernetes walks you through the advanced management of Kubernetes clusters. To start with, you will learn the fundamentals of both Kubernetes architecture and Kubernetes design in detail. You will discover how to run complex stateful microservices on Kubernetes including advanced features such as horizontal pod autoscaling, rolling updates, resource quotas, and persistent storage backend. Using real-world use cases, you will explore the options for network configuration, and understand how to set up, operate, and troubleshoot various Kubernetes networking plugins. In addition to this, you will get to grips with custom resource development and utilization in automation and maintenance workflows. To scale up your knowledge of Kubernetes, you will encounter some additional concepts based on the Kubernetes 1.10 release, such as Promethus, Role-based access control, API aggregation, and more. By the end of this book, you’ll know everything you need to graduate from intermediate to advanced level of understanding Kubernetes. Style and approach Delving into the design of the Kubernetes platform, the reader will be exposed to Kubernetes advanced features and best practices. This advanced-level book will provide a pathway to mastering Kubernetes.

Create visually appealing and feature-rich applications by using Qt 5 and the C++ language About This Book ? Explore Qt 5’s powerful features to easily design your GUI application ? Leverage Qt 5 to build attractive cross-platform applications ? Work with Qt modules for multimedia, networking, and location, to customize your Qt applications Who This Book Is For This book will appeal to developers and programmers who would like to build GUI-based applications. Basic knowledge of C++ is necessary and the basics of Qt would be helpful. What You Will Learn ? Implement tools provided by Qt 5 to design a beautiful GUI ? Understand different types of graphs and charts supported by Qt 5 ? Create a web browser using the Qt 5 WebEngine module and web view widget ? Connect to the MySQL database and display data obtained from it onto the Qt 5 GUI ? Incorporate the Qt 5 multimedia and networking module in your application ? Develop Google Map-like applications using Qt 5’s location module ? Discover cross-platform development by exporting the Qt 5 application to different platforms ? Uncover the secrets behind debugging Qt 5 and C++ applications In Detail Qt 5, the latest version of Qt, enables you to develop applications with complex user interfaces for multiple targets. It provides you with faster and smarter ways to create modern UIs and applications for multiple platforms. This book will teach you to design and build graphical user interfaces that are functional, appealing, and user-friendly. In the initial part of the book, you will learn what Qt 5 is and what you can do with it. You will explore the Qt Designer, discover the different types of widgets generally used in Qt 5, and then connect your application to the database to perform dynamic operations. Next, you will be introduced to Qt 5 chart which allows you to easily render different types of graphs and charts and incorporate List View Widgets in your application. You will also work with various Qt modules, like QtLocation, QtWebEngine, and the networking module through the course of the book. Finally, we will focus on cross-platform development with QT 5 that enables you to code once and run it everywhere, including mobile platforms. By the end of this book, you will have successfully learned about high-end GUI applications and will be capable of building many more powerful, cross-platform applications. Style and approach This is a comprehensive guide that explores the essential Qt features and implement them in building real-world cross-platform GUI applications

Create classic data structures and algorithms such as depth-first search and breadth-first search, learn recursion, as well as create and use a heap data structure using JavaScript About This Book ? Implement common data structures and the associated algorithms along with the context in which they are used ? Master existing JavaScript data structures such as arrays, sets, and maps, and learn how to implement new ones such as stacks, linked lists, trees, and graphs in ES 8 ? Develop abstract data types to make JavaScript a more flexible and powerful programming language Who This Book Is For If you’re a JavaScript developer who wants to dive deep into JavaScript and write complex programs using JavaScript data structures and algorithms, this book is for you. What You Will Learn ? Declare, initialize, add, and remove items from arrays, stacks, and queues ? Create and use linked lists, doubly linked lists, and circular linked lists ? Store unique elements with hash tables, dictionaries, and sets ? Explore the use of binary trees and binary search trees ? Sort data structures using algorithms such as bubble sort, selection sort, insertion sort, merge sort, and quick sort ? Search elements in data structures using sequential sort and binary search In Detail A data structure is a particular way of organizing data in a computer to utilize resources efficiently. Data structures and algorithms are the base of every solution to any programming problem. With this book, you will learn to write complex and powerful code using the latest ES 2017 features. Learning JavaScript Data Structures and Algorithms begins by covering the basics of JavaScript and introduces you to ECMAScript 2017, before gradually moving on to the most important data structures such as arrays, queues, stacks, and linked lists. You will gain in-depth knowledge of how hash tables and set data structures function as well as how trees and hash maps can be used to search files in an HD or represent a database. This book serves as a route to take you deeper into JavaScript. You’ll also get a greater understanding of why and how graphs, one of the most complex data structures, are largely used in GPS navigation systems in social networks. Toward the end of the book, you’ll discover how all the theories presented in this book can be applied to solve real-world problems while working on your own computer networks and Facebook searches. Style and approach Easy to follow guide which will cover the most used data structures and sorting/searching algorithms known in the computer science world along with examples to help the readers understand each chapter thoroughly.

Master Game UI system by creating captivating user interface components with Unity 5 through Unity 2018 and C#. Learn about UI texts, images, world space UI, mobile-specific UI and much more. About This Book ? Develop a game UI with both technical and aesthetic considerations ? Use all the UI elements provided by Unity's UI system ? Step-by-step examples of creating user interface components in the top game genres Who This Book Is For This book is for anyone keen to improve their games via a great user interface with Unity's UI system. If you're looking for a book that explains how to develop specific user interfaces or that thoroughly explains how each of the individual Unity components work, this book is for you. What You Will Learn ? Design principles and patterns for laying out elements in your UI ? Techniques that allow your UI to scale appropriately in different resolutions ? How to use automatic layouts to streamline your UI building process ? Properties of the Event System and how to appropriately hook events to your UI elements ? Access the components and properties of UI elements via code ? Implement all of Unity's built-in UI elements as well as those provided by TextMeshPro ? Develop key UI components that are popularly used in multiple game genres ? Add visual flare to user interfaces with the use of animation and particle effects ? Create a UI that displays in the Screen Space as well as World Space In Detail A functional UI is an important component for player interaction in every type of video game. Along with imparting crucial statistical information to the player, the UI is also the window through which the player engages with the world established by the game. Unity's tools give you the opportunity to create complex and attractive UIs to make your game stand out. This book helps you realize the full potential of Unity's powerful tools to create the best UI for your games by walking you through the creation of myriad user interface components. Learn how to create visually engaging heads-up-displays, pause menus, health bars, circular progress bars, animated menus, and more. This book not only teaches how to lay out visual elements, but also how to program these features and implement them across multiple games of varying genres. While working through the examples provided, you will learn how to develop a UI that scales to multiple screen resolutions, so your game can be released on multiple platforms with minimal changes. Style and approach The book walks you through the process of creating many different user interface components, by describing each UI component and property thoroughly and then providing step-by-step examples of its implementation. You will not only learn how to lay out visual elements, but you will also learn how to program for these features and hook them in to your game. The examples provided in the book can be reused for many other products.

Unleash Google's Cloud Platform to build, train and optimize machine learning models About This Book ? Get well versed in GCP pre-existing services to build your own smart models ? A comprehensive guide covering aspects from data processing, analyzing to building and training ML models ? A practical approach to produce your trained ML models and port them to your mobile for easy access Who This Book Is For This book is for data scientists, machine learning developers and AI developers who want to learn Google Cloud Platform services to build machine learning applications. Since the interaction with the Google ML platform is mostly done via the command line, the reader is supposed to have some familiarity with the bash shell and Python scripting. Some understanding of machine learning and data science concepts will be handy What You Will Learn ? Use Google Cloud Platform to build data-based applications for dashboards, web, and mobile ? Create, train and optimize deep learning models for various data science problems on big data ? Learn how to leverage BigQuery to explore big datasets ? Use Google’s pre-trained TensorFlow models for NLP, image, video and much more ? Create models and architectures for Time series, Reinforcement Learning, and generative models ? Create, evaluate, and optimize TensorFlow and Keras models for a wide range of applications In Detail Google Cloud Machine Learning Engine combines the services of Google Cloud Platform with the power and flexibility of TensorFlow. With this book, you will not only learn to build and train different complexities of machine learning models at scale but also host them in the cloud to make predictions. This book is focused on making the most of the Google Machine Learning Platform for large datasets and complex problems. You will learn from scratch how to create powerful machine learning based applications for a wide variety of problems by leveraging different data services from the Google Cloud Platform. Applications include NLP, Speech to text, Reinforcement learning, Time series, recommender systems, image classification, video content inference and many other. We will implement a wide variety of deep learning use cases and also make extensive use of data related services comprising the Google Cloud Platform ecosystem such as Firebase, Storage APIs, Datalab and so forth. This will enable you to integrate Machine Learning and data processing features into your web and mobile applications. By the end of this book, you will know the main difficulties that you may encounter and get appropriate strategies to overcome these difficulties and build efficient systems. Style and approach An easy-to-follow step by step guide which will help you get to the grips with real-world applications of Google Cloud Machine Learning.

Practical recipes to implement cost-effective and scalable cloud solutions for your organization About This Book ? Implement Google Cloud services in your organization ? Leverage Google Cloud components to secure your organization’s data ? A recipe-based guide that promises hands-on experience in deploying a highly scalable and available environment Who This Book Is For This book is for IT professionals, engineers, and developers looking at implementing Google Cloud in their organizations. Administrators and architects planning to make their organization more efficient with Google Cloud will also find this book useful. Basic understanding of Cloud services and the Google Cloud platform is necessary. What You Will Learn ? Host a Python application on Google Compute Engine ? Host an application using Google Cloud Functions ? Migrate a MySQL DB to Cloud Spanner ? Configure a network for a highly available application on GCP ? Learn simple image processing using Storage and Cloud Functions ? Automate security checks using Policy Scanner ? Understand tools for monitoring a production environment in GCP ? Learn to manage multiple projects using service accounts In Detail Google Cloud Platform is a cloud computing platform that offers products and services to host applications using state-of-the art infrastructure and technology. You can build and host applications and websites, store data, and analyze data on Google's scalable infrastructure. This book follows a recipe-based approach, giving you hands-on experience to make the most of Google Cloud services. This book starts with practical recipes that explain how to utilize Google Cloud's common services. Then, you'll see how to make full use of Google Cloud components such as networking, security, management, and developer tools. Next, we'll deep dive into implementing core Google Cloud services into your organization, with practical recipes on App Engine, Compute Engine microservices with Cloud Functions, virtual networks, and Cloud Storage. Later, we'll provide recipes on implementing authentication and security, Cloud APIs, command-line management, deployment management, and the Cloud SDK. Finally, we'll cover administration troubleshooting tasks with the Compute and Container Engines and we'll show how to monitor your organization's efficiency with best practices. By the end of this book, you'll have a complete understanding of how to implement Google Cloud services in your organization with ease. Style and approach This book will quickly get you started with using Google Cloud Services.

Build fault-tolerant, robust, and distributed applications in Scala About This Book ? Understand and use the concepts of reactive programming to build distributed systems running on multiple nodes. ? Learn how reactive architecture reduces complexity throughout the development process. ? Get to grips with functional reactive programming and Reactive Microservices. Who This Book Is For This book is for Scala developers who would like to build fault-tolerant, scalable distributed systems. No knowledge of Reactive programming is required. What You Will Learn ? Understand the fundamental principles of Reactive and Functional programming ? Develop applications utilizing features of the Akka framework ? Explore techniques to integrate Scala, Akka, and Play together ? Learn about Reactive Streams with real-time use cases ? Develop Reactive Web Applications with Play, Scala, Akka, and Akka Streams ? Develop and deploy Reactive microservices using the Lagom framework and ConductR In Detail Reactive programming is a scalable, fast way to build applications, and one that helps us write code that is concise, clear, and readable. It can be used for many purposes such as GUIs, robotics, music, and others, and is central to many concurrent systems. This book will be your guide to getting started with Reactive programming in Scala. You will begin with the fundamental concepts of Reactive programming and gradually move on to working with asynchronous data streams. You will then start building an application using Akka Actors and extend it using the Play framework. You will also learn about reactive stream specifications, event sourcing techniques, and different methods to integrate Akka Streams into the Play Framework. This book will also take you one step forward by showing you the advantages of the Lagom framework while working with reactive microservices. You will also learn to scale applications using multi-node clusters and test, secure, and deploy your microservices to the cloud. By the end of the book, you will have gained the knowledge to build robust and distributed systems with Scala and Akka. Style and approach The book takes a pragmatic approach, showing you how to build a scalable distributed system using Scala and Akka.

Build smart, efficient, and fast enterprise-grade web implementation of the microservices architecture that can be easily scaled. About This Book ? Write easy-to-maintain lean and clean code with Kotlin for developing better microservices ? Scale your Microserivces in your own cloud with Docker and Docker Swarm ? Explore Spring 5 functional reactive web programming with Spring WebFlux Who This Book Is For If you are a Kotlin developer with a basic knowledge of microservice architectures and now want to effectively implement these services on enterprise-level web applications, then this book is for you What You Will Learn ? Understand microservice architectures and principles ? Build microservices in Kotlin using Spring Boot 2.0 and Spring Framework 5.0 ? Create reactive microservices that perform non-blocking operations with Spring WebFlux ? Use Spring Data to get data reactively from MongoDB ? Test effectively with JUnit and Kotlin ? Create cloud-native microservices with Spring Cloud ? Build and publish Docker images of your microservices ? Scaling microservices with Docker Swarm ? Monitor microservices with JMX ? Deploy microservices in OpenShift Online In Detail With Google's inclusion of first-class support for Kotlin in their Android ecosystem, Kotlin's future as a mainstream language is assured. Microservices help design scalable, easy-to-maintain web applications; Kotlin allows us to take advantage of modern idioms to simplify our development and create high-quality services. With 100% interoperability with the JVM, Kotlin makes working with existing Java code easier. Well-known Java systems such as Spring, Jackson, and Reactor have included Kotlin modules to exploit its language features. This book guides the reader in designing and implementing services, and producing production-ready, testable, lean code that's shorter and simpler than a traditional Java implementation. Reap the benefits of using the reactive paradigm and take advantage of non-blocking techniques to take your services to the next level in terms of industry standards. You will consume NoSQL databases reactively to allow you to create high-throughput microservices. Create cloud-native microservices that can run on a wide range of cloud providers, and monitor them. You will create Docker containers for your microservices and scale them. Finally, you will deploy your microservices in OpenShift Online. Style and approach This book guides the reader in designing and implementing services, achieving production- ready, testable, easy-to-maintain, lean code that's shorter and simpler than a traditional Java implementation.