Ubuntu 16 04 Lts Book in PDF, ePub and Kindle version is available to download in english. Read online anytime anywhere directly from your device. Click on the download button below to get a free pdf file of Ubuntu 16 04 Lts book. This book definitely worth reading, it is an incredibly well-written.
The "Ubuntu 16.04 LTS Desktop: Applications and Administration" covers the Ubuntu 16.04 LTS (Xenial Xerus) release, focusing on applications and administrative tools. The emphasis here is on what users will face when using Ubuntu, covering topics like installation, applications, software management, desktops, shell commands, network connections, and system administration tasks. The Ubuntu Desktop (Unity), Kubuntu, Ubuntu Mate, and Ubuntu GNOME desktops are examined in detail. 16.04 introduces several new features, as well as numerous smaller modifications. It is a long-term support release. The Ubuntu desktop with the Unity interface is examined in detail. Unity uses a launcher and a dash to manage access to applications and devices.
Want to learn a new skill? Expand the technology that you work with? This is the latest version of Neil's books on the Ubuntu operating system and revised to tech the newest version of Ubuntu (16.04 LTS). This book covers the basics of understanding how to use the latest long term support edition of Ubuntu (16.04 LTS). In this book we use Ubuntu 16.04 LTS to learn multiple fundamentals in using Linux and later will go through the process of creating a web server. 80% of websites are driven by Linux servers. Understanding the basics and expanding upon this will provide great career opportunities and a great skill as well. We start simple and the reader does not need any prior knowledge. We will make baby steps and slowly work ourselves up to configuring the Ubuntu Server to be a functional web server. There will still be much to learn, but within a few hours you can have your own Linux server setup, understand the basics, and also have WordPress loaded into it. We cover installing packages, creating files in nano, LAMP stack (Linux Apache MySQL PHP), and try to do so in a practical way so that you can finish this guide with something to show off. This book covers multiple ways to get started, including two different VPS providers, installing the OS onto a computer, and configuration a virtual machine using Oracle's VirtualBox.
Ubuntu Server 16. 04 LTS Percise by Shiv Kumar Goyal Pdf
This book is designed as an Ubuntu 16.04 LTS server administration and quick reference. The purpose of this book is to help the Ubuntu users in doing daily tasks weather it is basic or advanced tasks. The book contains lot of screen shots and output of commands to accomplice the required task. This book emphasis on practical aspect of Ubuntu administration therefore you will find procedures with required theory only. This book cover LVM, ftp, user administration, firewall, NFS, logs and software management etc.
Mastering Hyperledger Fabric by Narendranath Reddy Thota Pdf
Mastering Hyperledger Fabric. A one-stop solution to become Master in the Hyperledger Fabric Key Features Detailed Explanation of One way TLS and mutual TLS Detailed Explanation of docker sockets (docker.sock) Exposed functionalities of Fabric CLI’s and SDK’s Enterprise-level chaincode development A glimpse of Hyperledger Fabric 2.0 Advanced examples of Node and golang Fabric SDK Onboard new organization using Node.js SDK (No more CLI) CI/CD for chaincode (Install chaincode directly onto peers from GitHub using Node.js) Fabric setup explanation with Different real-time use cases Deployment of Hyperledger Fabric using docker swarm and Kubernetes Setup and configure caliper to check benchmarks Monitor consortium with Prometheus and grafana Monitor docker and docker swarm using swarmpit and logspout Logging consortium with ELK/EFK stack Some interesting open-source tools and some Bonus concepts Table of Contents Chapter1: Introduction to the Hyperledger Landscape Chapter2: The Disruptive Potential of TLS Chapter3: All about docker sockets Chapter4: Installation Guide Of Prerequisites Chapter5: All about fabric CLI Chapter6: All about SDK's (go lang and Node.js) Chapter7: Advanced Chaincode Development Chapter8: End to End fabric consortium with Solo consensus using docker with one use case Chapter9: End to End fabric Consortium with Kafka consensus using docker swarm with one use case Chapter10: End to End fabric Consortium with Raft consensus using Kubernetes with one use case Chapter11: Private Data Concepts, Consortium level ACL(Access Control Lists) and raft consensus mechanism Chapter12: Setup and Benchmark Blockchain Consortium Using Caliper Chapter13: Monitoring Consortium with Prometheus and grafana Chapter14: Logging Consortium with ELK Stack Chapter15: Glimpse of Hyperledger fabric 2.0 Chapter16: Some Interesting tools Who this Book is For This Book benefits Software Engineers who are ready to shift their focus to distributed technologies and Blockchain. This book provides a comprehensive view of Solution Architecture, so it will be easy for architects to architect their solution. CTO’s around the world want to add hyperledger fabric to their technology stack. Managers to cope up with the latest trend. Faculty Professors in order to get industry insights. Even Engineering Students who want to be ready with the latest technologies. Book Description Mastering Hyperledger Fabric is a craving topic for all Hyperledger Fabric Developers around the world. Hyperledger Fabric is an open-source project that helps organizations create and maintain permissioned distributed Blockchain consortiums. This book is for readers who are looking for Hyperledger offerings to build end-to-end projects with growing complexity and functionalities. This book will be a one-stop solution for all developers who want to build blockchain consortiums using Hyperledger Fabric. Topics include TLS, Unix sockets, caliper(Benchmark tool), raft consensus, advanced chaincode development, key collision and MVCC, chaincode access controls, chaincode encryption, node.js SDK, golang SDK, docker daemon API, private data concepts, onboarding organizations using node.js SDK, deploy hyperledger fabric using Kubernetes, deploy hyperledger fabric using docker swarm, monitoring hyperledger fabric, monitoring Kubernetes, monitoring docker swarm, logging hyperledger fabric. After reading this book the reader will be able to set up Production grade hyperledger fabric consortium using raft consensus mechanisms with monitoring using Prometheus and grafana, even logging. This book explains so many key concepts of hyperledger fabric including 2.0 and written with three years of hyperledger fabric production experience.
Hands-On Machine Learning on Google Cloud Platform by Giuseppe Ciaburro,V Kishore Ayyadevara,Alexis Perrier Pdf
Unleash Google's Cloud Platform to build, train and optimize machine learning models Key Features Get well versed in GCP pre-existing services to build your own smart models A comprehensive guide covering aspects from data processing, analyzing to building and training ML models A practical approach to produce your trained ML models and port them to your mobile for easy access Book Description Google Cloud Machine Learning Engine combines the services of Google Cloud Platform with the power and flexibility of TensorFlow. With this book, you will not only learn to build and train different complexities of machine learning models at scale but also host them in the cloud to make predictions. This book is focused on making the most of the Google Machine Learning Platform for large datasets and complex problems. You will learn from scratch how to create powerful machine learning based applications for a wide variety of problems by leveraging different data services from the Google Cloud Platform. Applications include NLP, Speech to text, Reinforcement learning, Time series, recommender systems, image classification, video content inference and many other. We will implement a wide variety of deep learning use cases and also make extensive use of data related services comprising the Google Cloud Platform ecosystem such as Firebase, Storage APIs, Datalab and so forth. This will enable you to integrate Machine Learning and data processing features into your web and mobile applications. By the end of this book, you will know the main difficulties that you may encounter and get appropriate strategies to overcome these difficulties and build efficient systems. What you will learn Use Google Cloud Platform to build data-based applications for dashboards, web, and mobile Create, train and optimize deep learning models for various data science problems on big data Learn how to leverage BigQuery to explore big datasets Use Google’s pre-trained TensorFlow models for NLP, image, video and much more Create models and architectures for Time series, Reinforcement Learning, and generative models Create, evaluate, and optimize TensorFlow and Keras models for a wide range of applications Who this book is for This book is for data scientists, machine learning developers and AI developers who want to learn Google Cloud Platform services to build machine learning applications. Since the interaction with the Google ML platform is mostly done via the command line, the reader is supposed to have some familiarity with the bash shell and Python scripting. Some understanding of machine learning and data science concepts will be handy
Security Standardisation Research by Cas Cremers,Anja Lehmann Pdf
This book constitutes the refereed proceedings of the 4th International Conference on Security Standardisation Research, SSR 2018, held in Darmstadt, Germany, in November 2018.The papers cover a range of topics in the field of security standardisation research, including cryptographic evaluation, standards development, analysis with formal methods, potential future areas of standardisation, and improving existing standards.
Pro DevOps with Google Cloud Platform by Pierluigi Riti Pdf
Use DevOps principles with Google Cloud Platform (GCP) to develop applications and services. This book builds chapter by chapter to a complete real-life scenario, explaining how to build, monitor, and maintain a complete application using DevOps in practice. Starting with core DevOps concepts, continuous integration, and continuous delivery, you’ll cover common tools including Jenkins, Docker, and Kubernetes in the context of a real microservices application to deploy in the cloud. You will also create a monitor for your cloud and see how to use its data to prevent errors and improve the stability of the system. By the end of Pro DevOps with Google Cloud Platform, you will be able to deploy, maintain, and monitor a real application with GCP. What You Will LearnBuild and deploy applications and services using DevOps on Google Cloud Platform Maintain a complete continuous integration (CI) and continuous delivery (CD) pipeline Use containerization with Docker and Kubernetes Carry out CD with GCP and Jenkins Create microservices with Jenkins, Docker, and Kubernetes Monitor your newly deployed application and its deployment and performance Set up security and manage your network with GCP Who This Book Is For Developers and software architects who want to implement DevOps in practice. Some prior programming experience is recommended as well as a basic knowledge of a Linux command-line environment.
Google Cloud Platform Administration by Ranjit Singh Thakurratan Pdf
Make the most of GCP’s offerings to manage your data center workload and optimize deployments Key FeaturesDiscover new techniques to administer, manage, and deploy applications on GCPUnderstand effective solutions for storing, retrieving, and deploying your container imagesExplore various offerings of GCP for operations and security Book Description On-premise data centers are costly to manage. If you need a data center but don’t want to deal with a physical one, Google Cloud Platform (GCP) is the solution. With GCP, you can build, test, and deploy applications on Google’s infrastructure. Google Cloud Platform Administration begins with GCP fundamentals, with the help of which you will deploy your first app and gain an understanding of Google Cloud architecture and services. Furthermore, you will learn how to manage Compute, networking, and storage resources. As you make your way through the book, you will learn how to track and manage GCP’s usage, monitoring, and billing access control. You will also be able to manage your GCP's access and permissions. In the concluding chapters, you will explore a list of different developer tools for managing and interacting with the GCP platform. By the end of this book, you will have learned how to effectively deploy workloads on GCP. What you will learnUnderstand all GCP Compute componentsDeploy and manage multiple GCP storage optionsManage and utilize the networking resources offered by GCPExplore the functionalities and features of the GCP Container Understand the workings of GCP operations such as monitoring and error reporting Discover an immune GCP using its identity and security optionsWho this book is for Google Cloud Platform Administration is for administrators, cloud architects, and engineers who want to leverage the upcoming Google Cloud Platform. Some basic understanding of cloud computing will be useful.
Enhance DevOps workflows by integrating the functionalities of Docker, Kubernetes, Spinnaker, Ansible, Terraform, Flux CD, CaaS, and more with the help of practical examples and expert tips Key Features Get up and running with containerization-as-a-service and infrastructure automation in the public cloud Learn container security techniques and secret management with Cloud KMS, Anchore Grype, and Grafeas Kritis Leverage the combination of DevOps, GitOps, and automation to continuously ship a package of software Book DescriptionContainers have entirely changed how developers and end-users see applications as a whole. With this book, you'll learn all about containers, their architecture and benefits, and how to implement them within your development lifecycle. You'll discover how you can transition from the traditional world of virtual machines and adopt modern ways of using DevOps to ship a package of software continuously. Starting with a quick refresher on the core concepts of containers, you'll move on to study the architectural concepts to implement modern ways of application development. You'll cover topics around Docker, Kubernetes, Ansible, Terraform, Packer, and other similar tools that will help you to build a base. As you advance, the book covers the core elements of cloud integration (AWS ECS, GKE, and other CaaS services), continuous integration, and continuous delivery (GitHub actions, Jenkins, and Spinnaker) to help you understand the essence of container management and delivery. The later sections of the book will take you through container pipeline security and GitOps (Flux CD and Terraform). By the end of this DevOps book, you'll have learned best practices for automating your development lifecycle and making the most of containers, infrastructure automation, and CaaS, and be ready to develop applications using modern tools and techniques.What you will learn Become well-versed with AWS ECS, Google Cloud Run, and Knative Discover how to build and manage secure Docker images efficiently Understand continuous integration with Jenkins on Kubernetes and GitHub actions Get to grips with using Spinnaker for continuous deployment/delivery Manage immutable infrastructure on the cloud with Packer, Terraform, and Ansible Explore the world of GitOps with GitHub actions, Terraform, and Flux CD Who this book is for If you are a software engineer, system administrator, or operations engineer looking to step into the world of DevOps within public cloud platforms, this book is for you. Existing DevOps engineers will also find this book useful as it covers best practices, tips, and tricks to implement DevOps with a cloud-native mindset. Although no containerization experience is necessary, a basic understanding of the software development life cycle and delivery will help you get the most out of the book.
Data Analytics with Google Cloud Platform by Murari Ramuka Pdf
Step-by-step guide to different data movement and processing techniques, using Google Cloud Platform Services Key Featuresa- Learn the basic concept of Cloud Computing along with different Cloud service provides with their supported Models (IaaS/PaaS/SaaS)a- Learn the basics of Compute Engine, App Engine, Container Engine, Project and Billing setup in the Google Cloud Platforma- Learn how and when to use Cloud DataFlow, Cloud DataProc and Cloud DataPrep a- Build real-time data pipeline to support real-time analytics using Pub/Sub messaging servicea- Setting up a fully managed GCP Big Data Cluster using Cloud DataProc for running Apache Spark and Apache Hadoop clusters in a simpler, more cost-efficient mannera- Learn how to use Cloud Data Studio for visualizing the data on top of Big Querya- Implement and understand real-world business scenarios for Machine Learning, Data Pipeline EngineeringDescriptionModern businesses are awash with data, making data driven decision-making tasks increasingly complex. As a result, relevant technical expertise and analytical skills are required to do such tasks. This book aims to equip you with enough knowledge of Cloud Computing in conjunction with Google Cloud Data platform to succeed in the role of a Cloud data expert.Current market is trending towards the latest cloud technologies, which is the need of the hour. Google being the pioneer, is dominating this space with the right set of cloud services being offered as part of GCP (Google Cloud Platform). At this juncture, this book will be very vital and will be cover all the services that are being offered by GCP, putting emphasis on Data services.What will you learnBy the end of the book, you will have come across different data services and platforms offered by Google Cloud, and how those services/features can be enabled to serve business needs. You will also see a few case studies to put your knowledge to practice and solve business problems such as building a real-time streaming pipeline engine, Scalable Datawarehouse on Cloud, fully managed Hadoop cluster on Cloud and enabling TensorFlow/Machine Learning API's to support real-life business problems. Remember to practice additional examples to master these techniques. Who this book is forThis book is for professionals as well as graduates who want to build a career in Google Cloud data analytics technologies. One stop shop for those who wish to get an initial to advance understanding of the GCP data platform. The target audience will be data engineers/professionals who are new, as well as those who are acquainted with the tools and techniques related to cloud and data space. a- Individuals who have basic data understanding (i.e. Data and cloud) and have done some work in the field of data analytics, can refer/use this book to master their knowledge/understanding.a- The highlight of this book is that it will start with the basic cloud computing fundamentals and will move on to cover the advance concepts on GCP cloud data analytics and hence can be referred across multiple different levels of audiences. Table of Contents1. GCP Overview and Architecture2. Data Storage in GCP 3. Data Processing in GCP with Pub/Sub and Dataflow 4. Data Processing in GCP with DataPrep and Dataflow5. Big Query and Data Studio6. Machine Learning with GCP7. Sample Use cases and ExamplesAbout the Author Murari Ramuka is a seasoned Data Analytics professional with 12+ years of experience in enabling data analytics platforms using traditional DW/BI and Cloud Technologies (Azure, Google Cloud Platform) to uncover hidden insights and maximize revenue, profitability and ensure efficient operations management. He has worked with several multinational IT giants like Capgemini, Cognizant, Syntel and Icertis.His LinkedIn Profile: https://www.linkedin.com/in/murari-ramuka-98a440a/
Use Linux containers as an alternative virtualization technique to virtualize your operating system environment. This book will cover LXC’s unmatched flexibility with virtualization and LXD’s smooth user experience. Practical LXC and LXD begins by introducing you to Linux containers (LXC and LXD). You will then go through use cases based on LXC and LXD. Next, you will see the internal workings of LXC and LXD by considering the repositories and templates used. You will then learn how to integrate LXC and LXD with common virtualization and orchestration tools such as libvirt and SaltStack. Finally, you will dive into containerization and security. The book will explore some of the common problems in security and provide a case study on how containerization can help mitigate some of the operating system-level security issues in an IoT environment. What You Will Learn Get an introduction to Linux containers Discover the basics of LXC and LXD See use cases that can be solved with LXC and LXD – for developers, devops, and system administrators Master LXC and LXD repositories Use LXC and LXD with common virtualization and orchestration tools Consider a containerization and security in IoT case study Who This Book Is For The audience for this book should have basic knowledge of Linux and software development in general. The intended readership is primarily software developers, operations engineers, and system administrators who are interested in devops, though managers and enthusiasts will also benefit from this book.
TensorFlow 1.x Deep Learning Cookbook by Antonio Gulli,Amita Kapoor Pdf
Take the next step in implementing various common and not-so-common neural networks with Tensorflow 1.x About This Book Skill up and implement tricky neural networks using Google's TensorFlow 1.x An easy-to-follow guide that lets you explore reinforcement learning, GANs, autoencoders, multilayer perceptrons and more. Hands-on recipes to work with Tensorflow on desktop, mobile, and cloud environment Who This Book Is For This book is intended for data analysts, data scientists, machine learning practitioners and deep learning enthusiasts who want to perform deep learning tasks on a regular basis and are looking for a handy guide they can refer to. People who are slightly familiar with neural networks, and now want to gain expertise in working with different types of neural networks and datasets, will find this book quite useful. What You Will Learn Install TensorFlow and use it for CPU and GPU operations Implement DNNs and apply them to solve different AI-driven problems. Leverage different data sets such as MNIST, CIFAR-10, and Youtube8m with TensorFlow and learn how to access and use them in your code. Use TensorBoard to understand neural network architectures, optimize the learning process, and peek inside the neural network black box. Use different regression techniques for prediction and classification problems Build single and multilayer perceptrons in TensorFlow Implement CNN and RNN in TensorFlow, and use it to solve real-world use cases. Learn how restricted Boltzmann Machines can be used to recommend movies. Understand the implementation of Autoencoders and deep belief networks, and use them for emotion detection. Master the different reinforcement learning methods to implement game playing agents. GANs and their implementation using TensorFlow. In Detail Deep neural networks (DNNs) have achieved a lot of success in the field of computer vision, speech recognition, and natural language processing. The entire world is filled with excitement about how deep networks are revolutionizing artificial intelligence. This exciting recipe-based guide will take you from the realm of DNN theory to implementing them practically to solve the real-life problems in artificial intelligence domain. In this book, you will learn how to efficiently use TensorFlow, Google's open source framework for deep learning. You will implement different deep learning networks such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Deep Q-learning Networks (DQNs), and Generative Adversarial Networks (GANs) with easy to follow independent recipes. You will learn how to make Keras as backend with TensorFlow. With a problem-solution approach, you will understand how to implement different deep neural architectures to carry out complex tasks at work. You will learn the performance of different DNNs on some popularly used data sets such as MNIST, CIFAR-10, Youtube8m, and more. You will not only learn about the different mobile and embedded platforms supported by TensorFlow but also how to set up cloud platforms for deep learning applications. Get a sneak peek of TPU architecture and how they will affect DNN future. By using crisp, no-nonsense recipes, you will become an expert in implementing deep learning techniques in growing real-world applications and research areas such as reinforcement learning, GANs, autoencoders and more. Style and approach This book consists of hands-on recipes where you'll deal with real-world problems. You'll execute a series of tasks as you walk through data mining challenges using TensorFlow 1.x. Your one-stop solution for common and not-so-common pain points, this is a book that you must have on the shelf.
This book is designed as an Ubuntu 16.04 server reference, covering the Ubuntu servers and their support applications. Server tools are covered as well as the underlying configuration files and system implementations. The emphasis is on what administrators will need to know to perform key server support and management tasks. Coverage of the systemd service management system is integrated into the book, replacing the deprecated Upstart system. Topics covered include software management, systemd service management, AppArmor security, and the Network Time Protocol. Key servers are examined, including Web (Apache), FTP (vsftpd), printing (CUPS), NFS, and Samba (Windows). Network support servers and applications covered include the Squid proxy server, the Domain Name System (BIND) server, DHCP, firewalls (IPtables and FirewallD), and cloud computing.
Emerging Topics and Questions in Infocommunication Technologies by Sergey Balandin,Vladimir Deart,Valtteri Niemi Pdf
This collection of essays consists of selected papers presented at the 24th IEEE FRUCT conference. It highlights the most pressing research topics in infocommunication technologies, such as challenges in the development of next generation networks, the architectures and design of innovative knowledge-based systems, and innovations in healthcare and eHealth.
