Leverage the power of Kubernetes to build an efficient software delivery pipeline. Key Features * Learn about DevOps, containers, and Kubernetes all within one handy book * A practical guide to container management and orchestration * Learn how to monitor, log, and troubleshoot your Kubernetes applications Book Description Kubernetes has been widely adopted across public clouds and on-premise data centers. As we're living in an era of microservices, knowing how to use and manage Kubernetes is an essential skill for everyone in the IT industry. This book is a guide to everything you need to know about Kubernetes—from simply deploying a container to administrating Kubernetes clusters wisely. You'll learn about DevOps fundamentals, as well as deploying a monolithic application as microservices and using Kubernetes to orchestrate them. You will then gain an insight into the Kubernetes network, extensions, authentication and authorization. With the DevOps spirit in mind, you'll learn how to allocate resources to your application and prepare to scale them efficiently. Knowing the status and activity of the application and clusters is crucial, so we’ll learn about monitoring and logging in Kubernetes. Having an improved ability to observe your services means that you will be able to build a continuous delivery pipeline with confidence. At the end of the book, you'll learn how to run managed Kubernetes services on three top cloud providers: Google Cloud Platform, Amazon Web Services, and Microsoft Azure. What you will learn * Learn fundamental and advanced DevOps skills and tools * Get a comprehensive understanding of containers * Dockerize an application * Administrate and manage Kubernetes cluster * Extend the cluster functionality with custom resources * Understand Kubernetes network and service mesh * Implement Kubernetes logging and monitoring * Manage Kubernetes services in Amazon Web Services, Google Cloud Platform,and Microsoft Azure Who this book is for This book is for anyone who wants to learn containerization and clustering in a practical way using Kubernetes. No prerequisite skills are required, however, essential DevOps skill and public/private Cloud knowledge will accelerate the reading speed. If you're advanced, you can get a deeper understanding of all the tools and technique described in the book.

Stay updated with expert techniques for solving data analytics and machine learning challenges and gain insights from complex projects and power up your applications Key Features * Build independent machine learning (ML) systems leveraging the best features of R 3.5 * Understand and apply different machine learning techniques using real-world examples * Use methods such as multi-class classification, regression, and clustering Book Description Given the growing popularity of the R-zerocost statistical programming environment, there has never been a better time to start applying ML to your data. This book will teach you advanced techniques in ML ,using? the latest code in R 3.5. You will delve into various complex features of supervised learning, unsupervised learning, and reinforcement learning algorithms to design efficient and powerful ML models. This newly updated edition is packed with fresh examples covering a range of tasks from different domains. Mastering Machine Learning with R starts by showing you how to quickly manipulate data and prepare it for analysis. You will explore simple and complex models and understand how to compare them. You’ll also learn to use the latest library support, such as TensorFlow and Keras-R, for performing advanced computations. Additionally, you’ll explore complex topics, such as natural language processing (NLP), time series analysis, and clustering, which will further refine your skills in developing applications. Each chapter will help you implement advanced ML algorithms using real-world examples. You’ll even be introduced to reinforcement learning, along with its various use cases and models. In the concluding chapters, you’ll get a glimpse into how some of these blackbox models can be diagnosed and understood. By the end of this book, you’ll be equipped with the skills to deploy ML techniques in your own projects or at work. What you will learn * Prepare data for machine learning methods with ease * Understand how to write production-ready code and package it for use * Produce simple and effective data visualizations for improved insights * Master advanced methods, such as Boosted Trees and deep neural networks * Use natural language processing to extract insights in relation to text * Implement tree-based classifiers, including Random Forest and Boosted Tree Who this book is for This book is for data science professionals, machine learning engineers, or anyone who is looking for the ideal guide to help them implement advanced machine learning algorithms. The book will help you take your skills to the next level and advance further in this field. Working knowledge of machine learning with R is mandatory.

Build, secure, and deploy real-world serverless applications in AWS and peek into the serverless cloud offerings from Azure, Google Cloud, and IBM Cloud Key Features * Build serverless applications with AWS Lambda, AWS CloudFormation and AWS CloudWatch * Perform data analytics and natural language processing(NLP)on the AWS serverless platform * Explore various design patterns and best practices involved in serverless computing Book Description Managing physical servers will be a thing of the past once you’re able to harness the power of serverless computing. If you’re already prepped with the basics of serverless computing, Serverless Programming Cookbook will help you take the next step ahead. This recipe-based guide provides solutions to problems you might face while building serverless applications. You'll begin by setting up Amazon Web Services (AWS), the primary cloud provider used for most recipes. The next set of recipes will cover various components to build a Serverless application including REST APIs, database, user management, authentication, web hosting, domain registration, DNS management, CDN, messaging, notifications and monitoring. The book also introduces you to the latest technology trends such as Data Streams, Machine Learning and NLP. You will also see patterns and practices for using various services in a real world application. Finally, to broaden your understanding of Serverless computing, you'll also cover getting started guides for other cloud providers such as Azure, Google Cloud Platform and IBM cloud. By the end of this book, you’ll have acquired the skills you need to build serverless applications efficiently using various cloud offerings. What you will learn * Serverless computing in AWS and explore services with other clouds * Develop full-stack apps with API Gateway, Cognito, Lambda and DynamoDB * Web hosting with S3, CloudFront, Route 53 and AWS Certificate Manager * SQS and SNS for effective communication between microservices * Monitoring and troubleshooting with CloudWatch logs and metrics * Explore Kinesis Streams, Amazon ML models and Alexa Skills Kit Who this book is for For developers looking for practical solutions to common problems while building a serverless application, this book provides helpful recipes. To get started with this intermediate-level book, knowledge of basic programming is a must.

Unearth the power of GraphQL, React, Apollo, Node, and Express to build a scalable, production ready application Key Features * Build full stack applications with modern APIs using GraphQL and Apollo * Integrate Apollo into React and build frontend components using GraphQL * Implement a self-updating notification pop-up with a unique GraphQL feature called Subscriptions Book Description React, one of the most widely used JavaScript frameworks, allows developers to build fast and scalable front end applications for any use case. GraphQL is the modern way of querying an API. It represents an alternative to REST and is the next evolution in web development. Combining these two revolutionary technologies will give you a future-proof and scalable stack you can start building your business around. This book will guide you in implementing applications by using React, Apollo, Node.js and SQL. We'll focus on solving complex problems with GraphQL, such as abstracting multi-table database architectures and handling image uploads. Our client, and server will be powered by Apollo. Finally we will go ahead and build a complete Graphbook. While building the app, we'll cover the tricky parts of connecting React to the back end, and maintaining and synchronizing state. We'll learn all about querying data and authenticating users. We'll write test cases to verify the front end and back end functionality for our application and cover deployment. By the end of the book, you will be proficient in using GraphQL and React for your full-stack development requirements. What you will learn * Resolve data from multi-table database and system architectures * Build a GraphQL API by implementing models and schemas with Apollo and Sequelize * Set up an Apollo Client and build front end components using React * Use Mocha to test your full-stack application * Write complex React components and share data across them * Deploy your application using Docker Who this book is for The book is for web developers who want to enhance their skills and build complete full stack applications using industry standards. Familiarity with JavaScript, React, and GraphQL is expected to get the most from this book.

Create responsive eLearning content, including quizzes, demonstrations, simulations and Virtual Reality projects that fit on any device with Adobe Captivate 2019 Key Features * Build responsive, interactive and highly engaging eLearning content with Adobe Captivate 2019 * Build Virtual Reality eLearning experiences with Adobe Captivate 2019 * Assess your student knowledge with interactive and random quizzes * Seamlessly integrate your eLearning content with any SCORM or xAPI compliant LMS Book Description Adobe Captivate is used to create highly engaging, interactive, and responsive eLearning content. This book takes you through the production of a few pieces of eLearning content, covering all the project types and workflows of Adobe Captivate. First, you will learn how to create a typical interactive Captivate project. This will give you the opportunity to review all Captivate objects and uncover the application's main tools. Then, you will use the built-in capture engine of Captivate to create an interactive software simulation and a Video Demo that can be published as an MP4 video. Then, you will approach the advanced responsive features of Captivate to create a project that can be viewed on any device. And finally, you will immerse your learners in a 360o environment by creating Virtual Reality projects of Adobe Captivate. At the end of the book, you will empower your workflow and projects with the newer and most advanced features of the application, including variables, advanced actions, JavaScript, and using Captivate 2019 with other applications. If you want to produce high quality eLearning content using a wide variety of techniques, implement eLearning in your company, enable eLearning on any device, assess the effectiveness of the learning by using extensive Quizzing features, or are simply interested in eLearning, this book has you covered! What you will learn * Learn how to use the objects in Captivate to build professional eLearning content * Enhance your projects by adding interactivity, animations, and more * Add multimedia elements, such as audio and video, to create engaging learning experiences * Use themes to craft a unique visual experience * Use question slides to create SCORM-compliant quizzes that integrate seamlessly with your LMS * Make your content fit any device with responsive features of Captivate * Create immersive 360° experiences with Virtual Reality projects of Captivate 2019 * Integrate Captivate with other applications (such as PowerPoint and Photoshop) to establish a professional eLearning production workflow * Publish your project in a wide variety of formats including HTML5 and Flash Who this book is for If you are a teacher, instructional designer, eLearning developer, or human resources manager who wants to implement eLearning, then this book is for you. A basic knowledge of your OS is all it takes to create the next generation of responsive eLearning content.

Learn advanced state-of-the-art deep learning techniques and their applications using popular Python libraries Key Features *Build a strong foundation in neural networks and deep learning with Python libraries *Explore advanced deep learning techniques and their applications across computer vision and NLP *Learn how a computer can navigate in complex environments with reinforcement learning Book Description With the surge in artificial intelligence in applications catering to both business and consumer needs, deep learning is more important than ever for meeting current and future market demands. With this book, you’ll explore deep learning, and learn how to put machine learning to use in your projects. This second edition of Python Deep Learning will get you up to speed with deep learning, deep neural networks, and how to train them with high-performance algorithms and popular Python frameworks. You’ll uncover different neural network architectures, such as convolutional networks, recurrent neural networks, long short-term memory (LSTM) networks, and capsule networks. You’ll also learn how to solve problems in the fields of computer vision, natural language processing (NLP), and speech recognition. You'll study generative model approaches such as variational autoencoders and Generative Adversarial Networks (GANs) to generate images. As you delve into newly evolved areas of reinforcement learning, you’ll gain an understanding of state-of-the-art algorithms that are the main components behind popular games Go, Atari, and Dota. By the end of the book, you will be well-versed with the theory of deep learning along with its real-world applications. What you will learn *Grasp the mathematical theory behind neural networks and deep learning processes *Investigate and resolve computer vision challenges using convolutional networks and capsule networks *Solve generative tasks using variational autoencoders and Generative Adversarial Networks *Implement complex NLP tasks using recurrent networks (LSTM and GRU) and attention models *Explore reinforcement learning and understand how agents behave in a complex environment *Get up to date with applications of deep learning in autonomous vehicles Who this book is for This book is for data science practitioners, machine learning engineers, and those interested in deep learning who have a basic foundation in machine learning and some Python programming experience. A background in mathematics and conceptual understanding of calculus and statistics will help you gain maximum benefit from this book.

Automate Windows server tasks with the powerful features of the PowerShell Language Key Features * Leverage PowerShell to automate complex Windows server tasks * Master new features such as DevOps, and containers, and speed up their performance using PowerShell * Improve PowerShell's usability, and control and manage Windows-based environments by working through exciting recipes Book Description Windows Server 2019 represents the latest version of Microsoft’s flagship server operating system. It also comes with PowerShell Version 5.1 and has a number of additional features that IT pros find useful. The book helps the reader learn how to use PowerShell and manage core roles, features, and services of Windows Server 2019. You will begin with creating a PowerShell Administrative Environment that has updated versions of PowerShell and the Windows Management Framework, updated versions of the .NET Framework, and third-party modules. Next, you will learn to use PowerShell to set up and configure Windows Server 2019 networking and also managing objects in the AD environment. You will also learn to set up a host to utilize containers and how to deploy containers. You will also be implementing different mechanisms for achieving desired state configuration along with getting well versed with Azure infrastructure and how to setup Virtual Machines, web sites, and shared files on Azure. Finally, you will be using some powerful tools you can use to diagnose and resolve issues with Windows Server 2019. By the end of the book, you will learn a lot of trips and tricks to automate your windows environment with PowerShell What you will learn * Perform key admin tasks on Windows Server 2019 * Employing best practices for writing PowerShell scripts and configuring Windows Server 2019 * Use the .NET Framework to achieve administrative scripting * Set up VMs, websites, and shared files on Azure * Report system performance using built-in cmdlets and WMI to obtain single measurements * Know the tools you can use to diagnose and resolve issues with Windows Server Who this book is for If you are a systems administrator, engineer, or an architect working with Windows Server 2016 interested in upgrading to Windows Server 2019 and automating tasks with PowerShell, then this book is for you. A basic knowledge of PowerShell is expected.

Begin writing graphical user interface(GUI) applications for building human machine interfaces with a clear understanding of key concepts of the Qt framework Key Features * Learn how to write, assemble, and build Qt application from the command line * Understand key concepts like Signals and Slots in Qt * Best practices and effective techniques for designing graphical user interfaces using Qt 5 Book Description Qt is a cross-platform application framework and widget toolkit that is used to create GUI applications that can run on different hardware and operating systems. The main aim of this book is to introduce Qt to the reader. Through the use of simple examples, we will walk you through building blocks without focusing too much on theory. Qt is a popular tool that can be used for building a variety of applications, such as web browsers, media players such as VLC, and Adobe Photoshop. Following Qt installation and setup, the book dives straight into helping you create your first application. You will be introduced to Widgets, Qt's interface building block, and the many varieties that are available for creating GUIs. Next, Qt's core concept of signals and slots are well illustrated with sufficient examples. The book further teaches you how to create custom widgets, signals and slots, and how to communicate useful information via dialog boxes. To cap everything off, you will be taken through writing applications that can connect to databases in order to persist data. By the end of the book, you should be well equipped to start creating your own Qt applications and confident enough to pick up more advanced Qt techniques and materials to hone your skills. What you will learn * Set up and configure your machine to begin developing Qt applications * Discover different widgets and layouts for constructing UIs * Understand the key concept of signals and slots * Understand how signals and slots help animate a GUI * Explore how to create customized widgets along with signals and slots * Understand how to subclass and create a custom windows application * Understand how to write applications that can talk to databases. Who this book is for Anyone trying to start development of graphical user interface application will find this book useful. One does not need prior exposure to other toolkits to understand this book. In order to learn from this book you should have basic knowledge of C++ and a good grasp of Object Oriented Programming. Familiarity with GNU/Linux will be very useful though it's not a mandatory skill.

Build complex, observable, and fault-tolerant serverless systems easily on Microsoft Azure. Key Features * Use serverless systems to help you fulfill complex requirements * Develop your knowledge of Azure Microsoft Serverless * Understand concepts with a hands-on approach and helpful examples Book Description Advanced Serverless Architectures with Microsoft Azure redefines your experience of designing serverless systems. It shows you how to tackle challenges of varying levels, not just the straightforward ones. You'll be learning how to deliver features quickly by building systems, which retain the scalability and benefits of serverless. You'll begin your journey by learning how to build a simple, completely serverless application. Then, you'll build a highly scalable solution using a queue, load messages onto the queue, and read them asynchronously. To boost your knowledge further, the book also features durable functions and ways to use them to solve errors in a complex system. You'll then learn about security by building a security solution from serverless components. Next, you’ll gain an understanding of observability and ways to leverage application insights to bring you performance benefits. As you approach the concluding chapters, you’ll explore chaos engineering and the benefits of resilience, by actively switching off a few of the functions within a complex system, submitting a request, and observing the resulting behavior. By the end of this book, you will have developed the skills you need to build and maintain increasingly complex systems that match evolving platform requirements. What you will learn * Understand what true serverless architecture is * Study how to extend and scale architectures until they become ‘complex' * Implement durable functions in your design * Improve the observability of your serverless architecture * Implement security solutions using serverless services * Learn how to ‘practise' chaos engineering in production Who this book is for Advanced Serverless Architectures with Microsoft Azure is is ideal if you want to build serverless systems with fewer outages and high performance using Azure. Familiarity with the C# syntax and Azure Functions and ARM templates will help you to benefit more from this book. Prior knowledge of basic front-end development, HTML JS, and CSS is beneficial but not essential. Some DevOps knowledge is also beneficial but not essential.

Understand and solve complex computational problems and write efficient code with Kotlin Key Features * Learn about important data structures such as lists, arrays, queues, and stacks * Design custom algorithms for real-life implementations * Identify suitable tools for different scenarios and deliver immediate results Book Description Data structures and algorithms are more than just theoretical concepts. They help you become familiar with computational methods for solving problems and writing logical code. Equipped with this knowledge, you can write efficient programs that run faster and use less memory. Hands-On Data Structures and Algorithms with Kotlin book starts with the basics of algorithms and data structures, helping you get to grips with the fundamentals and measure complexity. You'll then move on to exploring the basics of functional programming while getting used to thinking recursively. Packed with plenty of examples along the way, this book will help you grasp each concept easily. In addition to this, you'll get a clear understanding of how the data structures in Kotlin's collection framework work internally. By the end of this book, you will be able to apply the theory of data structures and algorithms to work out real-world problems. What you will learn * Understand the basic principles of algorithms and data structures * Explore general-purpose data structures with arrays and linked lists * Get to grips with the basics of stacks, queues, and double-ended queues * Understand functional programming and related data structures * Use performant searching and efficient sorting * Uncover how Kotlin's collection framework functions * Become adept at implementing different types of maps Who this book is for If you're a Kotlin developer who wants to learn the intricacies of implementing data structures and algorithms for scalable application development, this book is for you.

A comprehensive guide for MCSA Exam 70-740, that will help you prepare from day one to earn the valuable Microsoft Certificate Key Features * Leverage practice questions and mock tests to pass this certification with confidence * Learn to Install Windows Servers,implement high availability, and monitor server environments * Gain necessary skills to implement and configure storage and compute features Book Description MCSA: Windows Server 2016 certification is one of the most sought-after certifications for IT professionals, which includes working with Windows Server and performing administrative tasks around it. This book is aimed at the 70-740 certification and is part of Packt's three-book series on MCSA Windows Server 2016 certification, which covers Exam 70-740, Exam 70-741, and Exam 70-742. This book will cover exam objectives for the 70-740 exam, and starting from installing and configuring Windows Server 2016, Windows Server imaging and deployment to configuring and managing disks and volumes, implementing and configuring server storage and implementing Hyper-V. At the end of each chapter you will be provided test questions to revise your learnings which will boost your confidence in preparing for the actual certifications. By the end of this book, you will learn everything needed to pass the, MCSA Exam 70-740: Installation, Storage, and Compute with Windows Server 2016, certification. What you will learn * Install Windows Server 2016 * Upgrade and Migrate servers and workloads * Implement and configure server storage * Install and configure Hyper-V * Configure the virtual machine (VM) settings * Configure Hyper-V storage * Configure Hyper-V networking Who this book is for This book is ideal for system administrators interested in installing and configuring storage and compute features with Windows Sever 2016 and aiming to pass the 70-740 certification. Some experience with Windows Server in an enterprise environment is assumed.

Create dynamic dashboards to bring interactive data visualization to your enterprise using Qlik Sense Key Features * Implement various Qlik Sense features to create interactive dashboards * Analyze data easily and make business decisions faster using Qlik Sense * Perform self-service data analytics and geospatial analytics using an example-based approach Book Description Qlik Sense allows you to explore simple-to-complex data to reveal hidden insights and data relationships to make business-driven decisions. Hands-On Business Intelligence with Qlik Sense begins by helping you get to grips with underlying Qlik concepts and gives you an overview of all Qlik Sense’s features. You will learn advanced modeling techniques and learn how to analyze the data loaded using a variety of visualization objects. You’ll also be trained on how to share apps through Qlik Sense Enterprise and Qlik Sense Cloud and how to perform aggregation with AGGR. As you progress through the chapters, you’ll explore the stories feature to create data-driven presentations and update an existing story. This book will guide you through the GeoAnalytics feature with the geo-mapping object and GeoAnalytics connector. Furthermore, you’ll learn about the self-service analytics features and perform data forecasting using advanced analytics. Lastly, you’ll deploy Qlik Sense apps for mobile and tablet. By the end of this book, you will be well-equipped to run successful business intelligence applications using Qlik Sense's functionality, data modeling techniques, and visualization best practices. What you will learn * Discover how to load, reshape, and model data for analysis * Apply data visualization practices to create stunning dashboards * Make use of Python and R for advanced analytics * Perform geo-analysis to create visualizations using native objects * Learn how to work with AGGR and data stories Who this book is for If you’re a data analyst, BI developer, or interested in business intelligence and want to gain practical experience of working on Qlik Sense, this book is for you. You’ll also find it useful if you want to explore Qlik Sense’s next-generation applications for self-service business intelligence. No prior experience of working with Qlik Sense is required.

Build fast, robust, and maintainable modern full-stack web applications using MongoDB, Express, Angular, and Node.js. Key Features * Build highly scalable, asynchronous, and event-driven APIs * Develop a user authentication system with MEAN * Build a full-fledged application using the MEAN stack Book Description MongoDB, Express, Angular and Node.js Fundamentals is a practical guide to the tried-and-true production-ready MEAN stack, with tips and best practices. The book begins by demystifying the MEAN architecture. You’ll take a look at the features of the JavaScript libraries, technologies, and frameworks that make up a MEAN stack. With this book, you'll not only learn how to develop highly scalable, asynchronous, and event-driven APIs quickly with Express and Node.js, but you'll also be able put your full-stack skills to use by building two full-fledged MEAN applications from scratch. You’ll understand how to build a blogging application using the MEAN stack and get to grips with user authentication using MEAN. As you progress through the chapters, you’ll explore some old and new features of Angular, such as pipes, reactive forms, modules and optimizing apps, animations and unit testing, and much more. By the end of the book, you’ll get ready to take control of the MEAN stack and transform into a full-stack JavaScript developer, developing efficient web applications using Javascript technologies. What you will learn * Understand the MEAN architecture * Create RESTful APIs to complete CRUD tasks * Build a blogging application with basic features * Describe best practices to secure node applications * Implement authentication and authorization * Creating simple animations using Angular * Perform unit testing on Angular applications Who this book is for If you are a beginner or intermediate frontend developer who wants to become full-stack JavaScript developer, this book is ideal for you. You'll need some prior exposure to MongoDB as we skim over its basics before getting straight to work.

Write high-level abstractions while retaining full control of the hardware, performances, and maintainability. Key Features * Transform your ideas into modern C++ code, with both C++11 and C++17 * Explore best practices for creating high-performance solutions * Understand C++ basics and work with concrete real-world examples Book Description C++ Fundamentals begins by introducing you to the C++ syntax. You will study the semantics of variables along with their advantages and trade-offs, and see how they can be best used to write safe and efficient code. With the help of this book, you’ll be able to compile fully working C++ programs and understand how variables, references, and pointers can be used to manipulate the state of the program. Then you'll explore functions and classes — the features that C++ offers to organize a program — and use them to solve more complex problems such as functions and classes. You’ll also understand common pitfalls and modern best practices, especially the ones that diverge from the C++98 guideline. As you advance through the chapters, you’ll study the advantages of generic programming and write your own templates to make generic algorithms that work with any type. This C++ book will guide you in fully exploiting standard containers and understanding how to pick the appropriate container for each problem. You will even work with a variety of memory management tools in C++. By the end of this book, you will not only be able to write efficient code, but also be equipped to improve the readability, performance, and maintainability of your programs using standard algorithms. What you will learn * Work with the C++ compilation model and syntaxes * Apply best practices for writing functions and classes * Write safe, generic, and efficient code with templates * Explore the containers that C++ standard offers * Discover the new paradigms introduced with C++11, C++14, and C++17 * Get to grips with the core language features of C++ * Abstract complex problems using object-oriented programming in C++ Who this book is for If you’re a developer looking to learn a new powerful language or are familiar with C++ but want to update your knowledge with modern paradigms of C++11, C++14, and C++17, this book is for you. To easily understand the concepts in the book, you must be familiar with the basics of programming.

Enhance your career options with this well-crafted object-oriented programming language that enjoys the support of an enormous ecosystem of tools and libraries Key Features * Get introduced to Java, its features, and its ecosystem * Understand how Java uses object-oriented programming * Become an expert Java exception handler Book Description Since its inception, Java has stormed the programming world. Its features and functionalities provide developers with the tools needed to write robust cross-platform applications. Java Fundamentals introduces you to these tools and functionalities that will enable you to create Java programs. The book begins with an introduction to the language, its philosophy, and evolution over time, until the latest release. You'll learn how the javac/java tools work and what Java packages are - the way a Java program is usually organized. Once you are comfortable with this, you'll be introduced to advanced concepts of the language, such as control flow keywords. You'll explore object-oriented programming and the part it plays in making Java what it is. In the concluding chapters, you'll get to grips with classes, typecasting, and interfaces, and understand the use of data structures, arrays, strings, handling exceptions, and creating generics. By the end of this book, you will have learned to write programs, automate tasks, and follow advanced courses on algorithms and data structures or explore more advanced Java courses. What you will learn * Create and run Java programs * Use data types, data structures, and control flow in your code * Implement best practices while creating objects * Work with constructors and inheritance * Understand advanced data structures to organize and store data * Employ generics for stronger check-types during compilation * Learn to handle exceptions in your code Who this book is for Java Fundamentals is designed for tech enthusiasts who are familiar with some programming languages and want a quick introduction to the most important principles of Java.

Learn how to train popular deep learning architectures such as autoencoders, convolutional and recurrent neural networks while discovering how you can use deep learning models in your software applications with Microsoft Cognitive Toolkit Key Features * Understand the fundamentals of Microsoft Cognitive Toolkit and set up the development environment * Train different types of neural networks using Cognitive Toolkit and deploy it to production * Evaluate the performance of your models and improve your deep learning skills Book Description Cognitive Toolkit is a very popular and recently open sourced deep learning toolkit by Microsoft. Cognitive Toolkit is used to train fast and effective deep learning models. This book will be a quick introduction to using Cognitive Toolkit and will teach you how to train and validate different types of neural networks, such as convolutional and recurrent neural networks. This book will help you understand the basics of deep learning. You will learn how to use Microsoft Cognitive Toolkit to build deep learning models and discover what makes this framework unique so that you know when to use it. This book will be a quick, no-nonsense introduction to the library and will teach you how to train different types of neural networks, such as convolutional neural networks, recurrent neural networks, autoencoders, and more, using Cognitive Toolkit. Then we will look at two scenarios in which deep learning can be used to enhance human capabilities. The book will also demonstrate how to evaluate your models' performance to ensure it trains and runs smoothly and gives you the most accurate results. Finally, you will get a short overview of how Cognitive Toolkit fits in to a DevOps environment What you will learn * Set up your deep learning environment for the Cognitive Toolkit on Windows and Linux * Pre-process and feed your data into neural networks * Use neural networks to make effcient predictions and recommendations * Train and deploy effcient neural networks such as CNN and RNN * Detect problems in your neural network using TensorBoard * Integrate Cognitive Toolkit with Azure ML Services for effective deep learning Who this book is for Data Scientists, Machine learning developers, AI developers who wish to train and deploy effective deep learning models using Microsoft CNTK will find this book to be useful. Readers need to have experience in Python or similar object-oriented language like C# or Java.

Design a virtualized data center with VMware vSphere 6.7 Key Features * Get the first book on the market that helps you design a virtualized data center with VMware vSphere 6.7 * Learn how to create professional vSphere design documentation to ensure a successful implementation * A practical guide that will help you apply infrastructure design principles to vSphere design Book Description VMware is the industry leader in data center virtualization. The vSphere 6.x suite of products provides a robust and resilient platform to virtualize server and application workloads. This book uses proven infrastructure design principles and applies them to VMware vSphere 6.7 virtual data center design through short and focused recipes on each design aspect. The second edition of this book focused on vSphere 6.0. vSphere features released since then necessitate an updated design guide, which includes recipes for upgrading to 6.7, vCenter HA; operational improvements; cutting-edge, high-performance storage access such as RDMA and Pmem; security features such as encrypted vMotion and VM-level encryption; Proactive HA; HA Orchestrated Restart; Predictive DRS; and more. By the end of the book, you will be able to achieve enhanced compute, storage, network, and management capabilities for your virtual data center. What you will learn * Identify key factors related to a vSphere design * Mitigate security risks and meet compliance requirements in a vSphere design * Create a vSphere conceptual design by identifying technical and business requirements * Design for performance, availability, recoverability, manageability, and security * Map the logical resource design into the physical vSphere design * Create professional vSphere design documentation Who this book is for If you are an administrator or consultant interested in designing virtualized data center environments using VMware vSphere 6.x (or previous versions of vSphere and the supporting components), this book is for you.

Get to grips with processing large volumes of data and presenting it as engaging, interactive insights using Spark and Python. Key Features * Get a hands-on, fast-paced introduction to the Python data science stack * Explore ways to create useful metrics and statistics from large datasets * Create detailed analysis reports with real-world data Book Description Processing big data in real time is challenging due to scalability, information inconsistency, and fault tolerance. Big Data Analysis with Python teaches you how to use tools that can control this data avalanche for you. With this book, you'll learn practical techniques to aggregate data into useful dimensions for posterior analysis, extract statistical measurements, and transform datasets into features for other systems. The book begins with an introduction to data manipulation in Python using pandas. You'll then get familiar with statistical analysis and plotting techniques. With multiple hands-on activities in store, you'll be able to analyze data that is distributed on several computers by using Dask. As you progress, you'll study how to aggregate data for plots when the entire data cannot be accommodated in memory. You'll also explore Hadoop (HDFS and YARN), which will help you tackle larger datasets. The book also covers Spark and explains how it interacts with other tools. By the end of this book, you'll be able to bootstrap your own Python environment, process large files, and manipulate data to generate statistics, metrics, and graphs. What you will learn * Use Python to read and transform data into different formats * Generate basic statistics and metrics using data on disk * Work with computing tasks distributed over a cluster * Convert data from various sources into storage or querying formats * Prepare data for statistical analysis, visualization, and machine learning * Present data in the form of effective visuals Who this book is for Big Data Analysis with Python is designed for Python developers, data analysts, and data scientists who want to get hands-on with methods to control data and transform it into impactful insights. Basic knowledge of statistical measurements and relational databases will help you to understand various concepts explained in this book.

Apply cloud native patterns and practices to deliver responsive, resilient, elastic, and message-driven systems with confidence Key Features * Discover best practices for applying cloud native patterns to your cloud applications * Explore ways to effectively plan resources and technology stacks for high security and fault tolerance * Gain insight into core architectural principles using real-world examples Book Description Cloud computing has proven to be the most revolutionary IT development since virtualization. Cloud native architectures give you the benefit of more flexibility over legacy systems. This Learning Path teaches you everything you need to know for designing industry-grade cloud applications and efficiently migrating your business to the cloud. It begins by exploring the basic patterns that turn your database inside out to achieve massive scalability. You’ll learn how to develop cloud native architectures using microservices and serverless computing as your design principles. Then, you’ll explore ways to continuously deliver production code by implementing continuous observability in production. In the concluding chapters, you’ll learn about various public cloud architectures ranging from AWS and Azure to the Google Cloud Platform, and understand the future trends and expectations of cloud providers. By the end of this Learning Path, you’ll have learned the techniques to adopt cloud native architectures that meet your business requirements. This Learning Path includes content from the following Packt products: * Cloud Native Development Patterns and Best Practices by John Gilbert * Cloud Native Architectures by Erik Farr et al. What you will learn * Understand the difference between cloud native and traditional architecture * Automate security controls and configuration management * Minimize risk by evolving your monolithic systems into cloud native applications * Explore the aspects of migration, when and why to use it * Apply modern delivery and testing methods to continuously deliver production code * Enable massive scaling by turning your database inside out Who this book is for This Learning Path is designed for developers who want to progress into building cloud native systems and are keen to learn the patterns involved. Software architects, who are keen on designing scalable and highly available cloud native applications, will also find this Learning Path very useful. To easily grasp these concepts, you will need basic knowledge of programming and cloud computing.

Leverage the power of reward-based training for your deep learning models with Python Key Features * Understand Q-learning algorithms to train neural networks using Markov Decision Process (MDP) * Study practical deep reinforcement learning using Q-Networks * Explore state-based unsupervised learning for machine learning models Book Description Q-learning is a machine learning algorithm used to solve optimization problems in artificial intelligence (AI). It is one of the most popular fields of study among AI researchers. This book starts off by introducing you to reinforcement learning and Q-learning, in addition to helping you get familiar with OpenAI Gym as well as libraries such as Keras and TensorFlow. A few chapters into the book, you will gain insights into modelfree Q-learning and use deep Q-networks and double deep Q-networks to solve complex problems. This book will guide you in exploring use cases such as self-driving vehicles and OpenAI Gym’s CartPole problem. You will also learn how to tune and optimize Q-networks and their hyperparameters. As you progress, you will understand the reinforcement learning approach to solving real-world problems. You will also explore how to use Q-learning and related algorithms in real-world applications such as scientific research. Toward the end, you’ll gain a sense of what’s in store for reinforcement learning. By the end of this book, you will be equipped with the skills you need to solve reinforcement learning problems using Q-learning algorithms with OpenAI Gym, Keras, and TensorFlow. What you will learn * Explore the fundamentals of reinforcement learning and the state-action-reward process * Understand Markov decision processes * Get well versed with libraries such as Keras, and TensorFlow * Create and deploy model-free learning and deep Q-learning agents with TensorFlow, Keras, and OpenAI Gym * Choose and optimize a Q-Network’s learning parameters and fine-tune its performance * Discover real-world applications and use cases of Q-learning Who this book is for If you are a machine learning developer, engineer, or professional who wants to delve into the deep learning approach for a complex environment, then this is the book for you. Proficiency in Python programming and basic understanding of decision-making in reinforcement learning is assumed.

Explore the exciting world of machine learning with the fastest growing technology in the world Key Features * Understand various machine learning concepts with real-world examples * Implement a supervised machine learning pipeline from data ingestion to validation * Gain insights into how you can use machine learning in everyday life Book Description Machine learning—the ability of a machine to give right answers based on input data—has revolutionized the way we do business. Applied Supervised Learning with Python provides a rich understanding of how you can apply machine learning techniques in your data science projects using Python. You'll explore Jupyter Notebooks, the technology used commonly in academic and commercial circles with in-line code running support. With the help of fun examples, you'll gain experience working on the Python machine learning toolkit—from performing basic data cleaning and processing to working with a range of regression and classification algorithms. Once you’ve grasped the basics, you'll learn how to build and train your own models using advanced techniques such as decision trees, ensemble modeling, validation, and error metrics. You'll also learn data visualization techniques using powerful Python libraries such as Matplotlib and Seaborn. This book also covers ensemble modeling and random forest classifiers along with other methods for combining results from multiple models, and concludes by delving into cross-validation to test your algorithm and check how well the model works on unseen data. By the end of this book, you'll be equipped to not only work with machine learning algorithms, but also be able to create some of your own! What you will learn * Understand the concept of supervised learning and its applications * Implement common supervised learning algorithms using machine learning Python libraries * Validate models using the k-fold technique * Build your models with decision trees to get results effortlessly * Use ensemble modeling techniques to improve the performance of your model * Apply a variety of metrics to compare machine learning models Who this book is for Applied Supervised Learning with Python is for you if you want to gain a solid understanding of machine learning using Python. It'll help if you to have some experience in any functional or object-oriented language and a basic understanding of Python libraries and expressions, such as arrays and dictionaries.