Learn the art of designing, implementing, and managing Cisco's networking solutions on datacenters, wirelessly, security and mobility to set up an Enterprise network. About This Book ? Implement Cisco's networking solutions on datacenters and wirelessly, Cloud, Security, and Mobility ? Leverage Cisco IOS to manage network infrastructures. ? A practical guide that will show how to troubleshoot common issues on the network. Who This Book Is For This book is targeted at network designers and IT engineers who are involved in designing, configuring, and operating enterprise networks, and are in taking decisions to make the necessary network changes to meet newer business needs such as evaluating new technology choices, enterprise growth, and adding new services on the network. The reader is expected to have a general understanding of the fundamentals of networking, including the OSI stack and IP addressing. What You Will Learn ? Understand the network lifecycle approach ? Get to know what makes a good network design ? Design components and technology choices at various places in the network (PINS) ? Work on sample configurations for network devices in the LAN/ WAN/ DC, and the wireless domain ? Get familiar with the configurations and best practices for securing the network ? Explore best practices for network operations In Detail Most enterprises use Cisco networking equipment to design and implement their networks. However, some networks outperform networks in other enterprises in terms of performance and meeting new business demands, because they were designed with a visionary approach. The book starts by describing the various stages in the network lifecycle and covers the plan, build, and operate phases. It covers topics that will help network engineers capture requirements, choose the right technology, design and implement the network, and finally manage and operate the network. It divides the overall network into its constituents depending upon functionality, and describe the technologies used and the design considerations for each functional area. The areas covered include the campus wired network, wireless access network, WAN choices, datacenter technologies, and security technologies. It also discusses the need to identify business-critical applications on the network, and how to prioritize these applications by deploying QoS on the network. Each topic provides the technology choices, and the scenario, involved in choosing each technology, and provides configuration guidelines for configuring and implementing solutions in enterprise networks. Style and approach A step-by-step practical guide that ensures you implement Cisco solutions such as enterprise networks, cloud, and data centers, on small-to-large organizations.

Practical, hands-on solutions in Python to overcome any problem in Machine Learning About This Book ? Master the advanced concepts, methodologies, and use cases of machine learning ? Build ML applications for analytics, NLP and computer vision domains ? Solve the most common problems in building machine learning models Who This Book Is For This book is for the intermediate users such as machine learning engineers, data engineers, data scientists, and more, who want to solve simple to complex machine learning problems in their day-to-day work and build powerful and efficient machine learning models. A basic understanding of the machine learning concepts and some experience with Python programming is all you need to get started with this book. What You Will Learn ? Select the right algorithm to derive the best solution in ML domains ? Perform predictive analysis effciently using ML algorithms ? Predict stock prices using the stock index value ? Perform customer analytics for an e-commerce platform ? Build recommendation engines for various domains ? Build NLP applications for the health domain ? Build language generation applications using different NLP techniques ? Build computer vision applications such as facial emotion recognition In Detail Machine learning (ML) helps you find hidden insights from your data without the need for explicit programming. This book is your key to solving any kind of ML problem you might come across in your job. You’ll encounter a set of simple to complex problems while building ML models, and you'll not only resolve these problems, but you’ll also learn how to build projects based on each problem, with a practical approach and easy-to-follow examples. The book includes a wide range of applications: from analytics and NLP, to computer vision domains. Some of the applications you will be working on include stock price prediction, a recommendation engine, building a chat-bot, a facial expression recognition system, and many more. The problem examples we cover include identifying the right algorithm for your dataset and use cases, creating and labeling datasets, getting enough clean data to carry out processing, identifying outliers, overftting datasets, hyperparameter tuning, and more. Here, you'll also learn to make more timely and accurate predictions. In addition, you'll deal with more advanced use cases, such as building a gaming bot, building an extractive summarization tool for medical documents, and you'll also tackle the problems faced while building an ML model. By the end of this book, you'll be able to fine-tune your models as per your needs to deliver maximum productivity. Style and approach This book is a step-by-step guide on how to develop machine learning applications for various domains. Each chapter of this book contains the practical guide on how to build specific machine learning applications from its base-line approach to the best possible approach. Basic necessary concepts, conman mistakes for every approach and optimization techniques are discussed for each application.

Unleash the power of the Raspberry Pi 3 board to create interesting IoT projects About This Book ? Learn how to interface various sensors and actuators with the Raspberry Pi 3 and send this data to the cloud. ? Explore the possibilities offered by the IoT by using the Raspberry Pi to upload measurements to Google Docs. ? A practical guide that will help you create a Raspberry Pi robot using IoT modules. Who This Book Is For If you're a developer or electronics engineer and are curious about the Internet of Things, then this is the book for you. With only a rudimentary understanding of electronics, the Raspberry Pi, or similar credit-card sized computers, and some programming experience, you will be taught to develop state-of-the-art solutions for the Internet of Things in an instant. What You Will Learn ? Understand the concept of IoT and get familiar with the features of Raspberry Pi ? Learn to integrate sensors and actuators with the Raspberry Pi ? Communicate with cloud and Raspberry using communication protocols such as HTTP and MQTT ? Build DIY projects using Raspberry Pi, JavaScript/node.js and cloud (AWS) ? Explore the best practices to ensure the security of your connected devices In Detail This book is designed to introduce you to IoT and Raspberry Pi 3. It will help you create interesting projects, such as setting up a weather station and measuring temperature and humidity using sensors; it will also show you how to send sensor data to cloud for visualization in real-time. Then we shift our focus to leveraging IoT for accomplishing complex tasks, such as facial recognition using the Raspberry Pi camera module, AWS Rekognition, and the AWS S3 service. Furthermore, you will master security aspects by building a security surveillance system to protect your premises from intruders using Raspberry Pi, a camera, motion sensors, and AWS Cloud. We'll also create a real-world project by building a Wi-Fi – controlled robot car with Raspberry Pi using a motor driver circuit, DC motor, and a web application. This book is a must-have as it provides a practical overview of IoT’s existing architectures, communication protocols, and security threats at the software and hardware levels—security being the most important aspect of IoT. Style and approach Internet of Things with the Raspberry Pi 3 contains the tools needed to design, sense the environment, communicate over the Internet, and visualize the results.

Leverage the power of PostgreSQL 10 to design, administer and maintain a high-performance database solution About This Book ? Obtain optimal PostgreSQL 10 database performance, ranging from initial design to routine maintenance ? Fine tune the performance of your queries and avoid the common pitfalls that can slow your system down ? Contains tips and tricks on scaling successful database installations, and ensuring a highly available PostgreSQL solution Who This Book Is For This book is designed for database administrators and PostgreSQL architects who already use or plan to exploit the features of PostgreSQL 10 to design and maintain a high-performance PostgreSQL database. A working knowledge of SQL, and some experience with PostgreSQL will be helpful in getting the most out of this book. What You Will Learn ? Learn best practices for scaling PostgreSQL 10 installations ? Discover the best hardware for developing high-performance PostgreSQL applications ? Benchmark your whole system – from hardware to application ? Learn by real examples how server parameters impact performance ? Discover PostgreSQL 10 features for partitioning and parallel query ? Monitor your server, both inside and outside the database ? Design and implement a good replication system on PostgreSQL 10 In Detail PostgreSQL database servers have a common set of problems that they encounter as their usage gets heavier and requirements get more demanding. Peek into the future of your PostgreSQL 10 database's problems today. Know the warning signs to look for and how to avoid the most common issues before they even happen. Surprisingly, most PostgreSQL database applications evolve in the same way—choose the right hardware, tune the operating system and server memory use, optimize queries against the database and CPUs with the right indexes, and monitor every layer, from hardware to queries, using tools from inside and outside PostgreSQL. Also, using monitoring insight, PostgreSQL database applications continuously rework the design and configuration. On reaching the limits of a single server, they break things up; connection pooling, caching, partitioning, replication, and parallel queries can all help handle increasing database workloads. By the end of this book, you will have all the knowledge you need to design, run, and manage your PostgreSQL solution while ensuring high performance and high availability Style and approach This book has been organized in such a manner that will help you understand basic PostgreSQL 10 performance tuning to an advanced-level configuration.

Combine the power of analytics and cloud computing for faster and efficient insights About This Book ? Master the concept of analytics on the cloud: and how organizations are using it ? Learn the design considerations and while applying a cloud analytics solution ? Design an end-to-end analytics pipeline on the cloud Who This Book Is For This book is targeted at CIOs, CTOs, and even analytics professionals looking for various alternatives to implement their analytics pipeline on the cloud. Data professionals looking to get started with cloud-based analytics will also find this book useful. Some basic exposure to cloud platforms such as GCP will be helpful, but not mandatory. What You Will Learn ? Explore the basics of cloud analytics and the major cloud solutions ? Learn how organizations are using cloud analytics to improve the ROI ? Explore the design considerations while adopting cloud services ? Work with the ingestion and storage tools of GCP such as Cloud Pub/Sub ? Process your data with tools such as Cloud Dataproc, BigQuery, etc ? Over 70 GCP tools to build an analytics engine for cloud analytics ? Implement machine learning and other AI techniques on GCP In Detail With the ongoing data explosion, more and more organizations all over the world are slowly migrating their infrastructure to the cloud. These cloud platforms also provide their distinct analytics services to help you get faster insights from your data. This book will give you an introduction to the concept of analytics on the cloud, and the different cloud services popularly used for processing and analyzing data. If you’re planning to adopt the cloud analytics model for your business, this book will help you understand the design and business considerations to be kept in mind, and choose the best tools and alternatives for analytics, based on your requirements. The chapters in this book will take you through the 70+ services available in Google Cloud Platform and their implementation for practical purposes. From ingestion to processing your data, this book contains best practices on building an end-to-end analytics pipeline on the cloud by leveraging popular concepts such as machine learning and deep learning. By the end of this book, you will have a better understanding of cloud analytics as a concept as well as a practical know-how of its implementation Style and approach Comprehensive guide with a perfect blend of theory, examples, and implementation of real-world use-cases

Get started with designing your serverless application using optimum design patterns and industry standard practices About This Book ? Learn the details of popular software patterns and how they are applied to serverless applications ? Understand key concepts and components in serverless designs ? Walk away with a thorough understanding of architecting serverless applications Who This Book Is For If you're a software architect, engineer, or someone who wants to build serverless applications, which are non-trivial in complexity and scope, then this book is for you. Basic knowledge of programming and serverless computing concepts are assumed. What You Will Learn ? Comprehend the popular design patterns currently being used with serverless architectures ? Understand the various design options and corresponding implementations for serverless web application APIs ? Learn multiple patterns for data-intensive serverless systems and pipelines, including MapReduce and Lambda Architecture ? Learn how to leverage hosted databases, queues, streams, storage services, and notification services ? Understand error handling and system monitoring in a serverless architecture a serverless architecture ? Learn how to set up a serverless application for continuous integration, continuous delivery, and continuous deployment In Detail Serverless applications handle many problems that developers face when running systems and servers. The serverless pay-per-invocation model can also result in drastic cost savings, contributing to its popularity. While it's simple to create a basic serverless application, it's critical to structure your software correctly to ensure it continues to succeed as it grows. Serverless Design Patterns and Best Practices presents patterns that can be adapted to run in a serverless environment. You will learn how to develop applications that are scalable, fault tolerant, and well-tested. The book begins with an introduction to the different design pattern categories available for serverless applications. You will learn the trade-offs between GraphQL and REST and how they fare regarding overall application design in a serverless ecosystem. The book will also show you how to migrate an existing API to a serverless backend using AWS API Gateway. You will learn how to build event-driven applications using queuing and streaming systems, such as AWS Simple Queuing Service (SQS) and AWS Kinesis. Patterns for data-intensive serverless application are also explained, including the lambda architecture and MapReduce. This book will equip you with the knowledge and skills you need to develop scalable and resilient serverless applications confidently. Style and approach Readers will be taken through a set of specific software patterns and learn, in detail, how to apply these patterns and build working software on top of a serverless system. At each step along the way, the reader will learn about the subcomponents and subsystems which comprise the larger system and which may be used in the future to solve different types of challenges.

A solution-based guide to put your deep learning models into production with the power of Apache Spark Key Features * Discover practical recipes for distributed deep learning with Apache Spark * Learn to use libraries such as Keras and TensorFlow * Solve problems in order to train your deep learning models on Apache Spark Book Description With deep learning gaining rapid mainstream adoption in modern-day industries, organizations are looking for ways to unite popular big data tools with highly efficient deep learning libraries. As a result, this will help deep learning models train with higher efficiency and speed. With the help of the Apache Spark Deep Learning Cookbook, you’ll work through specific recipes to generate outcomes for deep learning algorithms, without getting bogged down in theory. From setting up Apache Spark for deep learning to implementing types of neural net, this book tackles both common and not so common problems to perform deep learning on a distributed environment. In addition to this, you’ll get access to deep learning code within Spark that can be reused to answer similar problems or tweaked to answer slightly different problems. You will also learn how to stream and cluster your data with Spark. Once you have got to grips with the basics, you’ll explore how to implement and deploy deep learning models, such as Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN) in Spark, using popular libraries such as TensorFlow and Keras. By the end of the book, you'll have the expertise to train and deploy efficient deep learning models on Apache Spark. What you will learn * Set up a fully functional Spark environment * Understand practical machine learning and deep learning concepts * Apply built-in machine learning libraries within Spark * Explore libraries that are compatible with TensorFlow and Keras * Explore NLP models such as Word2vec and TF-IDF on Spark * Organize dataframes for deep learning evaluation * Apply testing and training modeling to ensure accuracy * Access readily available code that may be reusable Who this book is for If you’re looking for a practical and highly useful resource for implementing efficiently distributed deep learning models with Apache Spark, then the Apache Spark Deep Learning Cookbook is for you. Knowledge of the core machine learning concepts and a basic understanding of the Apache Spark framework is required to get the best out of this book. Additionally, some programming knowledge in Python is a plus.

Understand the Ethereum platform to build distributed applications that are secured and decentralized using blockchain technology Key Features *Build your own decentralized applications using real-world blockchain examples *Implement Ethereum for building smart contracts and cryptocurrency applications with easy-to-follow projects *Enhance your application security with blockchain Book Description Ethereum enables the development of efficient, smart contracts that contain code. These smart contracts can interact with other smart contracts to make decisions, store data, and send Ether to others.Ethereum Projects for Beginners provides you with a clear introduction to creating cryptocurrencies, smart contracts, and decentralized applications. As you make your way through the book, you’ll get to grips with detailed step-by-step processes to build advanced Ethereum projects. Each project will teach you enough about Ethereum to be productive right away. You will learn how tokenization works, think in a decentralized way, and build blockchain-based distributed computing systems. Towards the end of the book, you will develop interesting Ethereum projects such as creating wallets and secure data sharing.By the end of this book, you will be able to tackle blockchain challenges by implementing end-to-end projects using the full power of the Ethereum blockchain. What you will learn *Develop your ideas fast and efficiently using the Ethereum blockchain *Make writing and deploying smart contracts easy and manageable *Work with private data in blockchain applications *Handle large files in blockchain applications *Ensure your decentralized applications are safe *Explore how Ethereum development frameworks work *Create your own cryptocurrency or token on the Ethereum blockchain *Make sure your cryptocurrency is ERC20-compliant to launch an ICO Who this book is for This book is for individuals who want to build decentralized applications using blockchain technology and the power of Ethereum from scratch. Some prior knowledge of JavaScript is required, since most examples use a web frontend.

Explore powerful R packages to create predictive models using ensemble methods Key Features *Implement machine learning algorithms to build ensemble-efficient models *Explore powerful R packages to create predictive models using ensemble methods *Learn to build ensemble models on large datasets using a practical approach Book Description Ensemble techniques are used for combining two or more similar or dissimilar machine learning algorithms to create a stronger model. Such a model delivers superior prediction power and can give your datasets a boost in accuracy. Hands-On Ensemble Learning with R begins with the important statistical resampling methods. You will then walk through the central trilogy of ensemble techniques – bagging, random forest, and boosting – then you'll learn how they can be used to provide greater accuracy on large datasets using popular R packages. You will learn how to combine model predictions using different machine learning algorithms to build ensemble models. In addition to this, you will explore how to improve the performance of your ensemble models. By the end of this book, you will have learned how machine learning algorithms can be combined to reduce common problems and build simple efficient ensemble models with the help of real-world examples. What you will learn *Carry out an essential review of re-sampling methods, bootstrap, and jackknife *Explore the key ensemble methods: bagging, random forests, and boosting *Use multiple algorithms to make strong predictive models *Enjoy a comprehensive treatment of boosting methods *Supplement methods with statistical tests, such as ROC *Walk through data structures in classification, regression, survival, and time series data *Use the supplied R code to implement ensemble methods *Learn stacking method to combine heterogeneous machine learning models Who this book is for This book is for you if you are a data scientist or machine learning developer who wants to implement machine learning techniques by building ensemble models with the power of R. You will learn how to combine different machine learning algorithms to perform efficient data processing. Basic knowledge of machine learning techniques and programming knowledge of R would be an added advantage.

Master serverless architectures in Python and their implementation, with Zappa on three different frameworks. Key Features * Scalable serverless Python web services using Django, Flask, and Pyramid. * Learn Asynchronous task execution on AWS Lambda and scheduling using Zappa. * Implementing Zappa in a Docker container. Book Description Serverless applications are becoming very popular these days, not just because they save developers the trouble of managing the servers, but also because they provide several other benefits such as cutting heavy costs and improving the overall performance of the application. This book will help you build serverless applications in a quick and efficient way. We begin with an introduction to AWS and the API gateway, the environment for serverless development, and Zappa. We then look at building, testing, and deploying apps in AWS with three different frameworks--Flask, Django, and Pyramid. Setting up a custom domain along with SSL certificates and configuring them with Zappa is also covered. A few advanced Zappa settings are also covered along with securing Zappa with AWS VPC. By the end of the book you will have mastered using three frameworks to build robust and cost-efficient serverless apps in Python. What you will learn *Build, test, and deploy a simple web service using AWS CLI *Integrate Flask-based Python applications, via AWS CLI configuration *Design Rest APIs integrated with Zappa for Flask and Django *Create a project in the Pyramid framework and configure it with Zappa *Generate SSL Certificates using Amazon Certificate Manager *Configure custom domains with AWS Route 53 *Create a Docker container similar to AWS Lambda Who this book is for Python Developers who are interested in learning how to develop fast and highly scalable serverless applications in Python, will find this book useful

Use the two popular web development stacks, Node.js and MongoDB, to build full-featured web applications About This Book ? Learn the new ECMAScript along with Node 8 and MongoDB to make your application more effective. ? Get the up-to-date information required to launch your first application prototype using the latest versions of Node.js and MongoDB. ? A practical guide with clear instructions to designing and developing a complete web application from start to finish using trending frameworks such as angular4 and hapi Who This Book Is For The book is designed for JavaScript developers of any skill level who want to get up-and-running using Node.js and MongoDB to build full-featured web applications. A basic understanding of JavaScript and HTML is the only prerequisite for this book. What You Will Learn ? Work with Node.js building blocks ? Write and configure a web server using Node.js powered by the Express.js framework ? Build dynamic HTML pages using the Handlebars template engine ? Persist application data using MongoDB and Mongoose ODM ? Test your code using automated testing tools such as the Mocha framework ? Automate test cases using Gulp ? Reduce your web development time by integrating third-party tools for web interaction. ? Deploy a development environment to the cloud using services such as Heroku, Amazon Web Services, and Microsoft Azure ? Explore single-page application frameworks to take your web applications to the next level In Detail Node.js builds fast, scalable network applications while MongoDB is the perfect fit as a high-performance, open source NoSQL database solution. The combination of these two technologies offers high performance and scalability and helps in building fast, scalable network applications. Together they provide the power for manage any form of data as well as speed of delivery. This book will help you to get these two technologies working together to build web applications quickly and easily, with effortless deployment to the cloud. You will also learn about angular 4, which consumes pure JSON APOIs from a hapi server. The book begins by setting up your development environment, running you through the steps necessary to get the main application server up-and-running. Then you will see how to use Node.js to connect to a MongoDB database and perform data manipulations. From here on, the book will take you through integration with third-party tools to interact with web apps. You will see how to use controllers and view models to generate reusable code that will reduce development time. Toward the end, the book supplies tests to properly execute your code and take your skills to the next level with the most popular frameworks for developing web applications. By the end of the book, you will have a running web application developed with MongoDB, Node.js, and some of the most powerful and popular frameworks. Style and approach A practical guide with clear instructions to designing and developing a complete web application from start to finish

Learn the fundamentals of Java EE 8 APIs to build effective web services Key Features *Design modern and stylish web services with Java EE APIs *Secure your web services with JSON Web Tokens *Explore the advanced concepts of RESTful web services and the JAX-RS API Book Description Java Enterprise Edition is one of the leading application programming platforms for enterprise Java development. With Java EE 8 finally released and the first application servers now available, it is time to take a closer look at how to develop modern and lightweight web services with the latest API additions and improvements. Building RESTful Web Services with Java EE 8 is a comprehensive guide that will show you how to develop state-of-the-art RESTful web services with the latest Java EE 8 APIs. You will begin with an overview of Java EE 8 and the latest API additions and improvements. You will then delve into the details of implementing synchronous RESTful web services and clients with JAX-RS. Next up, you will learn about the specifics of data binding and content marshalling using the JSON-B 1.0 and JSON-P 1.1 APIs. This book also guides you in leveraging the power of asynchronous APIs on the server and client side, and you will learn to use server-sent events (SSEs) for push communication. The final section covers advanced web service topics such as validation, JWT security, and diagnosability. By the end of this book, you will have implemented several working web services and have a thorough understanding of the Java EE 8 APIs required for lightweight web service development. What you will learn *Dive into the latest Java EE 8 APIs relevant for developing web services *Use the new JSON-B APIs for easy data binding *Understand how JSON-P API can be used for flexible processing *Implement synchronous and asynchronous JAX-RS clients *Use server-sent events to implement server-side code *Secure Java EE 8 web services with JSON Web Tokens Who this book is for If you're a Java developer who wants to learn how to implement web services using the latest Java EE 8 APIs, this book is for you. Though no prior knowledge of Java EE 8 is required, experience with a previous Java EE version will be beneficial.

Over 50 recipes on the core features of Apache Mesos and running big data frameworks in Mesos About This Book ? Learn to install and configure Mesos to suit the needs of your organization ? Follow step-by-step instructions to deploy application frameworks on top of Mesos, saving you many hours of research and trial and error ? Use this practical guide packed with powerful recipes to implement Mesos and easily integrate it with other application frameworks Who This Book Is For This book is for system administrators, engineers, and big data programmers. Basic experience with big data technologies such as Hadoop or Spark would be useful but is not essential. A working knowledge of Apache Mesos is expected. What You Will Learn ? Set up Mesos on different operating systems ? Use the Marathon and Chronos frameworks to manage multiple applications ? Work with Mesos and Docker ? Integrate Mesos with Spark and other big data frameworks ? Use networking features in Mesos for effective communication between containers ? Configure Mesos for high availability using Zookeeper ? Secure your Mesos clusters with SASL and Authorization ACLs ? Solve everyday problems and discover the best practices In Detail Apache Mesos is open source cluster sharing and management software. Deploying and managing scalable applications in large-scale clustered environments can be difficult, but Apache Mesos makes it easier with efficient resource isolation and sharing across application frameworks. The goal of this book is to guide you through the practical implementation of the Mesos core along with a number of Mesos supported frameworks. You will begin by installing Mesos and then learn how to configure clusters and maintain them. You will also see how to deploy a cluster in a production environment with high availability using Zookeeper. Next, you will get to grips with using Mesos, Marathon, and Docker to build and deploy a PaaS. You will see how to schedule jobs with Chronos. We’ll demonstrate how to integrate Mesos with big data frameworks such as Spark, Hadoop, and Storm. Practical solutions backed with clear examples will also show you how to deploy elastic big data jobs. You will find out how to deploy a scalable continuous integration and delivery system on Mesos with Jenkins. Finally, you will configure and deploy a highly scalable distributed search engine with ElasticSearch. Throughout the course of this book, you will get to know tips and tricks along with best practices to follow when working with Mesos. Style and approach This step-by-step guide is packed with powerful recipes on using Apache Mesos and shows its integration with containers and big data frameworks.

Leverage the power of PowerShell to bring the best out of your AWS infrastructure About This Book ? A collection of real-world-tested Powershell *s that can be used to manage your Windows server efficiently ? Follow step-by-step processes to solve your problems with Windows servers using AWS tools ? Design examples that work in the Amazon free usage tier, which lets you run the Windows platform on cloud Who This Book Is For This book will be useful for (but not limited to) Windows System administrators, cloud engineers, architects, DevOps engineers, and all those who want to accomplish tasks on the AWS Public Cloud using PowerShell. What You Will Learn ? Install the AWS Tools for PowerShell 6 ? Understand key services provided by Amazon Web services (AWS) ? Understand the Virtual Private Cloud ? Use PowerShell 6 for AWS Identity and Access Management (IAM) ? Use PowerShell 6 for AWS Elastic Compute Cloud (EC2) ? Use PowerShell 6 for AWS Simple Storage Service (S3) ? Use PowerShell 6 for AWS Relational Database Service (RDS) ? Build fault-tolerant and highly-available applications using PowerShell 6 In Detail AWS Tools for PowerShell 6 shows you exactly how to automate all the aspects of AWS. You can take advantage of the amazing power of the cloud, yet add powerful *s and mechanisms to perform common tasks faster than ever before. This book expands on the Amazon documentation with real-world, useful examples and production-ready *s to automate all the aspects of your new cloud platform. It will cover topics such as managing Windows with PowerShell, setting up security services, administering database services, and deploying and managing networking. You will also explore advanced topics such as PowerShell authoring techniques, and configuring and managing storage and content delivery. By the end of this book, you will be able to use Amazon Web Services to automate and manage Windows servers. You will also have gained a good understanding of automating the AWS infrastructure using simple coding. Style and approach This step-by-step guide starts with simple examples then expands to full-blown administrative tasks leading to the efficient management of Windows servers. Each topic covers a section related to Amazon Web Services products, and the examples are built on one another to deliver a comprehensive library of *s for administrators.

Discover how to build full stack web applications with the Raspberry Pi 3 About This Book ? Leverage JavaScript, HTML5, and Cloud APIs to create visual representations and interactive web pages. ? Learn to install and use a Node.js-based web framework to develop Raspberry Pi 3-powered web applications. ? A step-by-step guide that will cover from setting up a embedded system to developing embedded, device-powered interactive web applications. Who This Book Is For This book is aimed at hobbyist, enthusiasts, and developers eager to develop embedded device-powered web applications. Prior programming experience with JavaScript, HTML5, and Node.JS will be beneficial. What You Will Learn ? Get up and running with your Raspberry Pi ? Go full stack! Learn about the end-to-end development process for web applications, right from the OS up to the actual HTML web interface ? Discover that JavaScript is one of the fastest growing languages today, and is the only language that can be used both on a browser and server. This book will empower you to develop in a complete JavaScript stack ? See that the IoT is everywhere!Connect your application to the outside world. Make use of sensors in your Raspberry Pi to give your application an edge, and unleash the full power of the Internet of Things ? Build a rich UI with beautiful charts and data visualizations that can run on any browser ? Make your software data-driven. Learn how to utilize SQLite to collect and analyze data from multiple systems In Detail Modern web technology and portable computing together have enabled huge advances in the Internet of Things (IoT) space,as well as in areas such as machine learning and big data. The Raspberry Pi is a very popular portable computer for running full stack web applications. This book will empower you to master this rapidly evolving technology to develop complex web applications and interfaces. This book starts by familiarizing you with the various components that make up the web development stack and that will integrate into your Raspberry Pi-powered web applications. It also introduces the Raspberry Pi computer and teach you how to get up and running with a brand new one. Next, this book introduces you to the different kinds of sensor you’ll use to make your applications; using these skills, you will be able to create full stack web applications and make them available to users via a web interface. Later, this book will also teach you how to build interactive web applications using JavaScript and HTML5 for the visual representation of sensor data. Finally, this book will teach you how to use a SQLite database to store and retrieve sensor data from multiple Raspberry Pi computers. By the end of this book you will be able to create complex full stack web applications on the Raspberry Pi 3 and will have improved your application’s performance and usability. Style and approach Step-by-step instructions on developing a full stack web application and deploying it to the Cloud.

Learn how to build advanced reports and dashboards in Salesforce Lightning experience About This Book ? Visualize and create advanced reports and dashboards using Lightning Experience ? Improve overall business efficiency with advanced and effective reports and dashboards ? Understand and create custom reports and dashboards Who This Book Is For This book is targeted at Salesforce.com administrators, business analysts, and managers who use Salesforce.com for their daily job and want to learn in depth about Salesforce Reporting and Dashboard in Lightning Experience. Readers should have a basic knowledge of Salesforce, such as: Accounts, Contacts, Leads, Opportunities and custom objects. What You Will Learn ? Navigate in Salesforce.com within the Lightning Experience user interface ? Secure and share your reports and dashboards with other users ? Create, manage, and maintain reports using Report Builder ? Learn how the report type can affect the report generated ? Explore the report and dashboard folder and the sharing model ? Create reports with multiple formats and custom report types ? Explore various dashboard features in Lightning Experience ? Use Salesforce1, including accessing reports and dashboards In Detail Built on the Salesforce App Cloud, the new Lightning Experience combines the new Lightning Design System, Lightning App Builder, and Lightning Components to enable anyone to quickly and easily create modern enterprise apps. The book will start with a gentle introduction to the basics of Salesforce reports and dashboards. It will also explain how to access reports in depth. Then you will learn how to create and manage reports, to use Schedule Report, and create advanced report configurations. The next section talks about dashboards and will enable you to understand and compare various types of dashboard component and how you can benefit the most from each of them. Then we move on to advanced topics and explain tips and tricks related to reports and dashboards, including reporting snapshots, report parameters, and collaboration. Finally, we will discuss how to access dashboards and reports from the Salesforce1 mobile app. Style and approach This comprehensive guide covers the advanced features of the all new Salesforce Lightning concepts and communicates them through a practical approach to explore the underlying concepts of how, when, and why to use them.

Powerful, independent recipes to build deep learning models in different application areas using R libraries About This Book ? Master intricacies of R deep learning packages such as mxnet & tensorflow ? Learn application on deep learning in different domains using practical examples from text, image and speech ? Guide to set-up deep learning models using CPU and GPU Who This Book Is For Data science professionals or analysts who have performed machine learning tasks and now want to explore deep learning and want a quick reference that could address the pain points while implementing deep learning. Those who wish to have an edge over other deep learning professionals will find this book quite useful. What You Will Learn ? Build deep learning models in different application areas using TensorFlow, H2O, and MXnet. ? Analyzing a Deep boltzmann machine ? Setting up and Analysing Deep belief networks ? Building supervised model using various machine learning algorithms ? Set up variants of basic convolution function ? Represent data using Autoencoders. ? Explore generative models available in Deep Learning. ? Discover sequence modeling using Recurrent nets ? Learn fundamentals of Reinforcement Leaning ? Learn the steps involved in applying Deep Learning in text mining ? Explore application of deep learning in signal processing ? Utilize Transfer learning for utilizing pre-trained model ? Train a deep learning model on a GPU In Detail Deep Learning is the next big thing. It is a part of machine learning. It's favorable results in applications with huge and complex data is remarkable. Simultaneously, R programming language is very popular amongst the data miners and statisticians. This book will help you to get through the problems that you face during the execution of different tasks and Understand hacks in deep learning, neural networks, and advanced machine learning techniques. It will also take you through complex deep learning algorithms and various deep learning packages and libraries in R. It will be starting with different packages in Deep Learning to neural networks and structures. You will also encounter the applications in text mining and processing along with a comparison between CPU and GPU performance. By the end of the book, you will have a logical understanding of Deep learning and different deep learning packages to have the most appropriate solutions for your problems. Style and approach Collection of hands-on recipes that would act as your all-time reference for your deep learning needs

Bring the performance and security of SQL Server to Linux About This Book ? Design and administer your SQL Server solution on the open source Linux platform ? Install, configure, and fine-tune your database application for maximum performance ? An easy-to-follow guide teaching you how to implement various SQL Server CTP 2.x offerings on Linux—from installation to administration Who This Book Is For This book is for the Linux users who want to learn SQL Server on their favorite Linux distributions. It is not important if you are experienced database user or a beginner as we are starting from scratch. However, it is recommended that you have basic knowledge about relational models. More advanced readers can pick the chapters of their interest and study specific topics immediately. Users from Windows platform can also benefit from this book to expand their frontiers and become equally efficient on both platforms. What You Will Learn ? Install and set up SQL Server CTP 2.x on Linux ? Create and work with database objects using SQL Server on Linux ? Configure and administer SQL Server on Linux-based systems ? Create and restore database back-ups ? Protect sensitive data using the built-in cryptographic features ? Optimize query execution using indexes ? Improve query execution time by more than 10x using in-memory OLTP ? Track row-versioning using temporal tables In Detail Microsoft's launch of SQL Server on Linux has made SQL Server a truly versatile platform across different operating systems and data-types, both on-premise and on-cloud. This book is your handy guide to setting up and implementing your SQL Server solution on the open source Linux platform. You will start by understanding how SQL Server can be installed on supported and unsupported Linux distributions. Then you will brush up your SQL Server skills by creating and querying database objects and implementing basic administration tasks to support business continuity, including security and performance optimization. This book will also take you beyond the basics and highlight some advanced topics such as in-memory OLTP and temporal tables. By the end of this book, you will be able to recognize and utilize the full potential of setting up an efficient SQL Server database solution in your Linux environment. Style and approach This book follows a step-by-step approach to teach readers the concepts of SQL Server on Linux using the bash command line and SQL programming language trough examples which can easily be adapted and applied in your own solutions.

Harness the power of the Cloud, leveraging the speed and scale of Azure Serverless computing About This Book ? Take advantage of the agility, scale, and cost-effectiveness of the cloud using Azure Serverless compute ? Build scalable, reliable, and cost-effecient applications with Serverless architecture and .NET ? Learn to use Azure functions to their fullest potential in .NET Who This Book Is For This book is for .NET developers who would like to learn about serverless architecture. Basic C# programming knowledge is assumed. What You Will Learn ? Understand the best practices of Serverless architecture ? Learn how how to deploy a Text Sentiment Evaluation application in an Azure Serverless environment ? Implement security, identity, and access control ? Take advantage of the speed of deployment in the cloud ? Configure application health monitoring, logging, and alerts ? Design your application to ensure cost effectiveness, high availability, and scale In Detail Serverless architecture allows you to build and run applications and services without having to manage the infrastructure. Many companies have started adopting serverless architecture for their applications to save cost and improve scalability. This book will be your companion in designing Serverless architecture for your applications using the .NET runtime, with Microsoft Azure as the cloud service provider. You will begin by understanding the concepts of Serverless architecture, its advantages and disadvantages. You will then set up the Azure environment and build a basic application using a sample text sentiment evaluation function. From here, you will be shown how to run services in a Serverless environment. We will cover the integration with other Azure and 3rd party services such as Azure Service Bus, as well as configuring dependencies on NuGet libraries, among other topics. After this, you will learn about debugging and testing your Azure functions, and then automating deployment from source control. Securing your application and monitoring its health will follow from there, and then in the final part of the book, you will learn how to Design for High Availability, Disaster Recovery and Scale, as well as how to take advantage of the cloud pay-as-you-go model to design cost-effective services. We will finish off with explaining how azure functions scale up against AWS Lambda, Azure Web Jobs, and Azure Batch compare to other types of compute-on-demand services. Whether you’ve been working with Azure for a while, or you’re just getting started, by the end of the book you will have all the information you need to set up and deploy applications to the Azure Serverless Computing environment. Style and approach This step-by-step guide shows you the concepts and features of Serverless architecture in Azure with .NET.

Architect and design data-intensive applications and, in the process, learn how to collect, process, store, govern, and expose data for a variety of use cases Key Features *Integrate the data-intensive approach into your application architecture *Create a robust application layout with effective messaging and data querying architecture *Enable smooth data flow and make the data of your application intensive and fast Book Description Are you an architect or a developer who looks at your own applications gingerly while browsing through Facebook and applauding it silently for its data-intensive, yet ?uent and efficient, behaviour? This book is your gateway to build smart data-intensive systems by incorporating the core data-intensive architectural principles, patterns, and techniques directly into your application architecture. This book starts by taking you through the primary design challenges involved with architecting data-intensive applications. You will learn how to implement data curation and data dissemination, depending on the volume of your data. You will then implement your application architecture one step at a time. You will get to grips with implementing the correct message delivery protocols and creating a data layer that doesn’t fail when running high traffic. This book will show you how you can divide your application into layers, each of which adheres to the single responsibility principle. By the end of this book, you will learn to streamline your thoughts and make the right choice in terms of technologies and architectural principles based on the problem at hand. What you will learn *Understand how to envision a data-intensive system *Identify and compare the non-functional requirements of a data collection component *Understand patterns involving data processing, as well as technologies that help to speed up the development of data processing systems *Understand how to implement Data Governance policies at design time using various Open Source Tools *Recognize the anti-patterns to avoid while designing a data store for applications *Understand the different data dissemination technologies available to query the data in an efficient manner *Implement a simple data governance policy that can be extended using Apache Falcon Who this book is for This book is for developers and data architects who have to code, test, deploy, and/or maintain large-scale, high data volume applications. It is also useful for system architects who need to understand various non-functional aspects revolving around Data Intensive Systems.

Become an advanced practitioner with this progressive set of master classes on application-oriented machine learning About This Book ? Comprehensive coverage of key topics in machine learning with an emphasis on both the theoretical and practical aspects ? More than 15 open source Java tools in a wide range of techniques, with code and practical usage. ? More than 10 real-world case studies in machine learning highlighting techniques ranging from data ingestion up to analyzing the results of experiments, all preparing the user for the practical, real-world use of tools and data analysis. Who This Book Is For This book will appeal to anyone with a serious interest in topics in Data Science or those already working in related areas: ideally, intermediate-level data analysts and data scientists with experience in Java. Preferably, you will have experience with the fundamentals of machine learning and now have a desire to explore the area further, are up to grappling with the mathematical complexities of its algorithms, and you wish to learn the complete ins and outs of practical machine learning. What You Will Learn ? Master key Java machine learning libraries, and what kind of problem each can solve, with theory and practical guidance. ? Explore powerful techniques in each major category of machine learning such as classification, clustering, anomaly detection, graph modeling, and text mining. ? Apply machine learning to real-world data with methodologies, processes, applications, and analysis. ? Techniques and experiments developed around the latest specializations in machine learning, such as deep learning, stream data mining, and active and semi-supervised learning. ? Build high-performing, real-time, adaptive predictive models for batch- and stream-based big data learning using the latest tools and methodologies. ? Get a deeper understanding of technologies leading towards a more powerful AI applicable in various domains such as Security, Financial Crime, Internet of Things, social networking, and so on. In Detail Java is one of the main languages used by practicing data scientists; much of the Hadoop ecosystem is Java-based, and it is certainly the language that most production systems in Data Science are written in. If you know Java, Mastering Machine Learning with Java is your next step on the path to becoming an advanced practitioner in Data Science. This book aims to introduce you to an array of advanced techniques in machine learning, including classification, clustering, anomaly detection, stream learning, active learning, semi-supervised learning, probabilistic graph modeling, text mining, deep learning, and big data batch and stream machine learning. Accompanying each chapter are illustrative examples and real-world case studies that show how to apply the newly learned techniques using sound methodologies and the best Java-based tools available today. On completing this book, you will have an understanding of the tools and techniques for building powerful machine learning models to solve data science problems in just about any domain. Style and approach A practical guide to help you explore machine learning—and an array of Java-based tools and frameworks—with the help of practical examples and real-world use cases.