- Table View
- List View
TensorFlow Reinforcement Learning Quick Start Guide: Get up and running with training and deploying intelligent, self-learning agents using Python
by Kaushik BalakrishnanLeverage the power of Tensorflow to Create powerful software agents that can self-learn to perform real-world tasks Key Features Explore efficient Reinforcement Learning algorithms and code them using TensorFlow and Python Train Reinforcement Learning agents for problems, ranging from computer games to autonomous driving. Formulate and devise selective algorithms and techniques in your applications in no time. Book Description Advances in reinforcement learning algorithms have made it possible to use them for optimal control in several different industrial applications. With this book, you will apply Reinforcement Learning to a range of problems, from computer games to autonomous driving. The book starts by introducing you to essential Reinforcement Learning concepts such as agents, environments, rewards, and advantage functions. You will also master the distinctions between on-policy and off-policy algorithms, as well as model-free and model-based algorithms. You will also learn about several Reinforcement Learning algorithms, such as SARSA, Deep Q-Networks (DQN), Deep Deterministic Policy Gradients (DDPG), Asynchronous Advantage Actor-Critic (A3C), Trust Region Policy Optimization (TRPO), and Proximal Policy Optimization (PPO). The book will also show you how to code these algorithms in TensorFlow and Python and apply them to solve computer games from OpenAI Gym. Finally, you will also learn how to train a car to drive autonomously in the Torcs racing car simulator. By the end of the book, you will be able to design, build, train, and evaluate feed-forward neural networks and convolutional neural networks. You will also have mastered coding state-of-the-art algorithms and also training agents for various control problems. What you will learn Understand the theory and concepts behind modern Reinforcement Learning algorithms Code state-of-the-art Reinforcement Learning algorithms with discrete or continuous actions Develop Reinforcement Learning algorithms and apply them to training agents to play computer games Explore DQN, DDQN, and Dueling architectures to play Atari's Breakout using TensorFlow Use A3C to play CartPole and LunarLander Train an agent to drive a car autonomously in a simulator Who this book is for Data scientists and AI developers who wish to quickly get started with training effective reinforcement learning models in TensorFlow will find this book very useful. Prior knowledge of machine learning and deep learning concepts (as well as exposure to Python programming) will be useful.
TensorFlow for Deep Learning: From Linear Regression to Reinforcement Learning
by Bharath Ramsundar Reza Bosagh ZadehLearn how to solve challenging machine learning problems with TensorFlow, Google’s revolutionary new software library for deep learning. If you have some background in basic linear algebra and calculus, this practical book introduces machine-learning fundamentals by showing you how to design systems capable of detecting objects in images, understanding text, analyzing video, and predicting the properties of potential medicines.TensorFlow for Deep Learning teaches concepts through practical examples and helps you build knowledge of deep learning foundations from the ground up. It’s ideal for practicing developers with experience designing software systems, and useful for scientists and other professionals familiar with scripting but not necessarily with designing learning algorithms.Learn TensorFlow fundamentals, including how to perform basic computationBuild simple learning systems to understand their mathematical foundationsDive into fully connected deep networks used in thousands of applicationsTurn prototypes into high-quality models with hyperparameter optimizationProcess images with convolutional neural networksHandle natural language datasets with recurrent neural networksUse reinforcement learning to solve games such as tic-tac-toeTrain deep networks with hardware including GPUs and tensor processing units
TensorFlow für Dummies (Für Dummies)
by Matthew ScarpinoTensorFlow ist Googles herausragendes Werkzeug für das maschinelle Lernen, und dieses Buch macht es zugänglich, selbst wenn Sie bisher wenig über neuronale Netze und Deep Learning wissen. Sie erfahren, auf welchen Prinzipien TensorFlow basiert und wie Sie mit TensorFlow Anwendungen 1.0 schreiben. Gleichzeitig lernen Sie die Konzepte des maschinellen Lernens kennen. Wenn Sie Softwareentwickler sind und TensorFlow in Zukunft einsetzen möchten, dann ist dieses Buch der richtige Einstieg für Sie. Greifen Sie auch zu, wenn Sie einfach mehr über das maschinelle Lernen erfahren wollen.
TensorFlow in Action
by Thushan GanegedaraUnlock the TensorFlow design secrets behind successful deep learning applications! Deep learning StackOverflow contributor Thushan Ganegedara teaches you the new features of TensorFlow 2 in this hands-on guide.In TensorFlow in Action you will learn: Fundamentals of TensorFlow Implementing deep learning networks Picking a high-level Keras API for model building with confidence Writing comprehensive end-to-end data pipelines Building models for computer vision and natural language processing Utilizing pretrained NLP models Recent algorithms including transformers, attention models, and ElMo In TensorFlow in Action, you'll dig into the newest version of Google's amazing TensorFlow framework as you learn to create incredible deep learning applications. Author Thushan Ganegedara uses quirky stories, practical examples, and behind-the-scenes explanations to demystify concepts otherwise trapped in dense academic papers. As you dive into modern deep learning techniques like transformer and attention models, you&’ll benefit from the unique insights of a top StackOverflow contributor for deep learning and NLP. About the technology Google&’s TensorFlow framework sits at the heart of modern deep learning. Boasting practical features like multi-GPU support, network data visualization, and easy production pipelines using TensorFlow Extended (TFX), TensorFlow provides the most efficient path to professional AI applications. And the Keras library, fully integrated into TensorFlow 2, makes it a snap to build and train even complex models for vision, language, and more. About the book TensorFlow in Action teaches you to construct, train, and deploy deep learning models using TensorFlow 2. In this practical tutorial, you&’ll build reusable skill hands-on as you create production-ready applications such as a French-to-English translator and a neural network that can write fiction. You&’ll appreciate the in-depth explanations that go from DL basics to advanced applications in NLP, image processing, and MLOps, complete with important details that you&’ll return to reference over and over. What's inside Covers TensorFlow 2.9 Recent algorithms including transformers, attention models, and ElMo Build on pretrained models Writing end-to-end data pipelines with TFX About the reader For Python programmers with basic deep learning skills. About the author Thushan Ganegedara is a senior ML engineer at Canva and TensorFlow expert. He holds a PhD in machine learning from the University of Sydney. Table of Contents PART 1 FOUNDATIONS OF TENSORFLOW 2 AND DEEP LEARNING 1 The amazing world of TensorFlow 2 TensorFlow 2 3 Keras and data retrieval in TensorFlow 2 4 Dipping toes in deep learning 5 State-of-the-art in deep learning: Transformers PART 2 LOOK MA, NO HANDS! DEEP NETWORKS IN THE REAL WORLD 6 Teaching machines to see: Image classification with CNNs 7 Teaching machines to see better: Improving CNNs and making them confess 8 Telling things apart: Image segmentation 9 Natural language processing with TensorFlow: Sentiment analysis 10 Natural language processing with TensorFlow: Language modeling PART 3 ADVANCED DEEP NETWORKS FOR COMPLEX PROBLEMS 11 Sequence-to-sequence learning: Part 1 12 Sequence-to-sequence learning: Part 2 13 Transformers 14 TensorBoard: Big brother of TensorFlow 15 TFX: MLOps and deploying models with TensorFlow
TensorFlow: Predict valuable insights of your data with TensorFlow
by Md. Rezaul KarimLearn how to solve real life problems using different methods like logic regression, random forests and SVM’s with TensorFlow.Key FeaturesUnderstand predictive analytics along with its challenges and best practices Embedded with assessments that will help you revise the concepts you have learned in this bookBook DescriptionPredictive analytics discovers hidden patterns from structured and unstructured data for automated decision making in business intelligence. Predictive decisions are becoming a huge trend worldwide, catering to wide industry sectors by predicting which decisions are more likely to give maximum results. TensorFlow, Google’s brainchild, is immensely popular and extensively used for predictive analysis.This book is a quick learning guide on all the three types of machine learning, that is, supervised, unsupervised, and reinforcement learning with TensorFlow. This book will teach you predictive analytics for high-dimensional and sequence data. In particular, you will learn the linear regression model for regression analysis. You will also learn how to use regression for predicting continuous values. You will learn supervised learning algorithms for predictive analytics. You will explore unsupervised learning and clustering using K-meansYou will then learn how to predict neighborhoods using K-means, and then, see another example of clustering audio clips based on their audio features. This book is ideal for developers, data analysts, machine learning practitioners, and deep learning enthusiasts who want to build powerful, robust, and accurate predictive models with the power of TensorFlow. This book is embedded with useful assessments that will help you revise the concepts you have learned in this book.What you will learnLearn TensorFlow features in a real-life problem, followed by detailed TensorFlow installation and configurationExplore computation graphs, data, and programming models also get an insight into an example of implementing linear regression model for predictive analyticsSolve the Titanic survival problem using logistic regression, random forests, and SVMs for predictive analyticsDig deeper into predictive analytics and find out how to take advantage of it to cluster records belonging to the certain group or class for a dataset of unsupervised observationsLearn several examples of how to apply reinforcement learning algorithms for developing predictive models on real-life datasetsWho this book is forThis book is aimed at developers, data analysts, machine learning practitioners, and deep learning enthusiasts who want to build powerful, robust, and accurate predictive models with the power of TensorFlow.
Tenth International Conference on Applications and Techniques in Cyber Intelligence: Volume 1 (Lecture Notes on Data Engineering and Communications Technologies #170)
by Jemal H. Abawajy Xiaolu Zhang Mohammed Atiquzzaman Zheng XuThis book presents innovative ideas, cutting-edge findings, and novel techniques, methods, and applications in a broad range of cybersecurity and cyberthreat intelligence areas. As our society becomes smarter, there is a corresponding need to secure our cyberfuture. The book describes approaches and findings that are of interest to business professionals and governments seeking to secure our data and underpin infrastructures, as well as to individual users.
Tenth International Conference on Applications and Techniques in Cyber Intelligence: Volume 2 (Lecture Notes on Data Engineering and Communications Technologies #169)
by Jemal H. Abawajy Xiaolu Zhang Mohammed Atiquzzaman Zheng XuThis book presents innovative ideas, cutting-edge findings, and novel techniques, methods, and applications in a broad range of cybersecurity and cyberthreat intelligence areas. As our society becomes smarter, there is a corresponding need to secure our cyberfuture. The book describes approaches and findings that are of interest to business professionals and governments seeking to secure our data and underpin infrastructures, as well as to individual users.
Teoria del Linguaggio Formale e degli Automi
by Ajit SinghIl libro contiene una trattazione approfondita di tutti gli argomenti relativi alla teoria del calcolo, come menzionato nei syllabus di B.E., M.C.A. e M.Sc. (Informatica) di varie università. Una quantità sufficiente di input teorici supportati da una serie di illustrazioni sono inclusi per coloro che sono profondamente interessati alla materia. Nei primi capitoli il libro presenta il materiale di base necessario per lo studio delle teorie degli automi. Esempi di argomenti inclusi sono: i linguaggi regolari e il Teorema di Kleene; gli automi minimi e i monoidi sintattici; il rapporto tra linguaggi senza contesto e automi pushdown; le macchine di Turing e la decidibilità. Questo libro facilita agli studenti uno stile di scrittura più informale, fornendo al contempo la copertura più accessibile della teoria degli automi, un trattamento solido sulla costruzione di prove, molte figure e diagrammi per aiutare a trasmettere le idee, e barre laterali per evidenziare il materiale correlato. Ogni capitolo offre un'abbondanza di esercizi per l'apprendimento pratico.
Teradata Cookbook: Over 85 recipes to implement efficient data warehousing solutions
by Abhinav Khandelwal Rajsekhar BhamidipatiData management and analytics simplified with Teradata Key Features Take your understanding of Teradata to the next level and build efficient data warehousing applications for your organization Covers recipes on data handling, warehousing, advanced querying and the administrative tasks in Teradata. Contains practical solutions to tackle common (and not-so-common) problems you might encounter in your day to day activities Book Description Teradata is an enterprise software company that develops and sells its eponymous relational database management system (RDBMS), which is considered to be a leading data warehousing solutions and provides data management solutions for analytics. This book will help you get all the practical information you need for the creation and implementation of your data warehousing solution using Teradata. The book begins with recipes on quickly setting up a development environment so you can work with different types of data structuring and manipulation function. You will tackle all problems related to efficient querying, stored procedure searching, and navigation techniques. Additionally, you’ll master various administrative tasks such as user and security management, workload management, high availability, performance tuning, and monitoring. This book is designed to take you through the best practices of performing the real daily tasks of a Teradata DBA, and will help you tackle any problem you might encounter in the process. What you will learn Understand Teradata's competitive advantage over other RDBMSs. Use SQL to process data stored in Teradata tables. Leverage Teradata’s available application utilities and parallelism to play with large datasets Apply various performance tuning techniques to optimize the queries. Acquire deeper knowledge and understanding of the Teradata Architecture. Easy steps to load, archive, restore data and implement Teradata protection features Gain confidence in running a wide variety of Data analytics and develop applications for the Teradata environment Who this book is for This book is for Database administrator's and Teradata users who are looking for a practical, one-stop resource to solve all their problems while handling their Teradata solution. If you are looking to learn the basic as well as the advanced tasks involved in Teradata querying or administration, this book will be handy. Some knowledge of relational database concepts will be helpful to get the best out of this book.
Terahertz Imaging for Biomedical Applications
by Brian W.-H. Ng Xiaoxia Yin Derek AbbottTerahertz biomedical imaging has become an area of interest due to its ability to simultaneously acquire both image and spectral information. Terahertz imaging systems are being commercialized, with increasing trials performed in a biomedical setting. As a result, advanced digital image processing algorithms are needed to assist screening, diagnosis, and treatment. "Pattern Recognition and Tomographic Reconstruction" presents these necessary algorithms, which will play a critical role in the accurate detection of abnormalities present in biomedical imaging. Terhazertz tomographic imaging and detection technology contributes to the ability to identify opaque objects with clear boundaries, and would be useful to both in vivo and ex vivo environments, making this book a must-read for anyone in the field of biomedical engineering and digital imaging.
Terminological Dictionary of Automatic Control, Systems and Robotics (Intelligent Systems, Control and Automation: Science and Engineering #104)
by Tadej Bajd Juš Kocijan Gorazd Karer Rihard Karba Mojca Žagar KarerThis dictionary contains terms from the fields of automatic control, which includes mathematical modelling, simulation of dynamic systems, automation technology with its corresponding elements, and robotics. It also includes signal processing, information technologies and production technologies.The terminological dictionary is primarily aimed at experts and students who deal with control technology and dynamic systems in both technical and non-technical domains. To be able to use the dictionary, at least basic knowledge in this field is required. In the dictionary users will find concise terminological definitions. A concept may be designated by different terms; therefore, cross-references are used. The aim of the dictionary is to collect and unify – at least to an achievable extent – the terminology in the field of automatic control, dynamic systems and robotics.
Terminologie: Zum 25-jährigen Bestehen des Rats für Deutschsprachige Terminologie (Kommunikation und Medienmanagement)
by Petra Drewer Donatella PulitanoAlle, die sich mit fachsprachlichen Texten beschäftigen, beschäftigen sich automatisch auch mit Terminologie: Beim Lesen von Fachtexten nehmen sie die darin enthaltene Terminologie auf, beim Verfassen von Fachtexten verwenden oder produzieren sie Terminologie, beim Fachübersetzen übertragen sie Terminologie in andere Sprachen.Im Laufe der Zeit haben sich Methoden und Verfahren entwickelt, wie man professionell und effizient mit Terminologie arbeitet. Die Auseinandersetzung mit den Grundsätzen der Terminologiearbeit hat sich zu einer wissenschaftlichen Disziplin entwickelt.Der Rat für Deutschsprachige Terminologie (RaDT) wurde 1994 als Initiative der UNESCO-Kommissionen Deutschlands, Österreichs und der Schweiz gegründet, um terminologische Aktivitäten zu fördern. Zu seinem 25-jährigen Bestehen erscheint nun dieser Sammelband, der einen Überblick über das vielfältige Schaffen und das gesamte Themenspektrum der RaDT-Mitglieder bietet.Um die verschiedenen Perspektiven innerhalb der RaDT-Gemeinschaft angemessen wiederzugeben, umfasst der Band vier Themenbereiche:1. Vielfalt an Epochen2. Vielfalt an Schwerpunkten3. Vielfalt an Umsetzungen (in öffentlichen Institutionen)4. Vielfalt an Umsetzungen (in der Privatwirtschaft)Dieser Sammelband richtet sich an alle, die sich mit Terminologie, Terminologiewissenschaft oder Terminologiearbeit befassen, insbesondere in Unternehmensbereichen wie Sprachmanagement, Terminologiemanagement, Corporate Language, Wissensmanagement, sowie an Studierende und Wissenschaftler in den entsprechenden Disziplinen.
Terminology Saturation: Detection, Measurement and Use (Cognitive Science and Technology)
by Vadim Ermolayev Victoria KosaThis book highlights an innovative approach for extracting terminological cores from subject domain-bounded collections of professional texts. The approach is based on exploiting the phenomenon of terminological saturation. The book presents the formal framework for the method of detecting and measuring terminological saturation as a successive approximation process. It further offers the suite of the algorithms that implement the method in the software and comprehensively evaluates all the aspects of the method and possible input configurations in the experiments on synthetic and real collections of texts in several subject domains. The book demonstrates the use of the developed method and software pipeline in industrial and academic use cases. It also outlines the potential benefits of the method for the adoption in industry.
Terms of Service: Social Media and the Price of Constant Connection
by Jacob SilvermanSocial networking has grown into a staple of modern society, but its continued evolution is becoming increasingly detrimental to our lives. Shifts in communication and privacy are affecting us more than we realize or understand. Terms of Service crystalizes this current moment in technology and contemplates its implications: the identity-validating pleasures and perils of online visibility; our newly adopted view of daily life through the lens of what is share-worthy; and the surveillance state operated by social media platforms—Facebook, Google, Twitter, and others—to mine our personal data for advertising revenue, an invasion of our lives that is as pervasive as government spying.Jacob Silverman calls for social media users to take back ownership of their digital selves from the Silicon Valley corporations who claim to know what's best for them. Integrating politics, sociology, national security, pop culture, and technology, he reveals the surprising conformity at the heart of Internet culture—explaining how social media companies engineer their products to encourage shallow engagement and discourage dissent. Reflecting on the collapsed barriers between our private and public lives, Silverman brings into focus the inner conflict we feel when deciding what to share and what to "like," and explains how we can take the steps we need to free ourselves from its grip.
Terraform Cookbook: Efficiently define, launch, and manage Infrastructure as Code across various cloud platforms
by Mikael KriefThis book is for developers, operators, and DevOps engineers looking to improve their workflow and use Infrastructure as Code. Experience with Microsoft Azure, Jenkins, shell scripting, and DevOps practices is required to get the most out of this Terraform book.
Terraform Cookbook: Master Infrastructure as Code efficiency with real-world Azure automation using Terraform
by Mikael KriefExplore how to provision, manage, and scale your infrastructure using Infrastructure as Code (IaC) with Terraform Purchase of the print or Kindle book includes a free PDF eBookKey FeaturesGet up and running with Terraform (v1+) CLI and automate infrastructure provisioningDiscover how to deploy Kubernetes resources with TerraformBecome a Terraform troubleshooting expert for streamlined infrastructure management and minimal downtimeBook DescriptionImagine effortlessly provisioning complex cloud infrastructure across various cloud platforms, all while ensuring robustness, reusability, and security. Introducing the Terraform Cookbook, Second Edition - your go-to guide for mastering Infrastructure as Code (IaC) effortlessly. This new edition is packed with real-world examples for provisioning robust Cloud infrastructure mainly across Azure but also with a dedicated chapter for AWS and GCP. You will delve into manual and automated testing with Terraform configurations, creating and managing a balanced, efficient, reusable infrastructure with Terraform modules. You will learn how to automate the deployment of Terraform configurations through continuous integration and continuous delivery (CI/CD), unleashing Terraform's full potential. New chapters have been added that describe the use of Terraform for Docker and Kubernetes, and explain how to test Terraform configurations using different tools to check code and security compliance. The book devotes an entire chapter to achieving proficiency in Terraform Cloud, covering troubleshooting strategies for common issues and offering resolutions to frequently encountered errors. Get the insider knowledge to boost productivity with Terraform - the indispensable guide for anyone adopting Infrastructure as Code solutions.What you will learnUse Terraform to build and run cloud and Kubernetes infrastructure using IaC best practicesAdapt the Terraform command line adapted to appropriate use casesAutomate the deployment of Terraform confi guration with CI/CDDiscover manipulation of the Terraform state by adding or removing resourcesExplore Terraform for Docker and Kubernetes deployment, advanced topics on GitOps practices, and Cloud Development Kit (CDK)Add and apply test code and compliance security in Terraform configurationDebug and troubleshoot common Terraform errorsWho this book is forThis book is for developers, operators, and DevOps engineers looking to improve their workflow and use Infrastructure as Code. If you find yourself spending too much time on manual infrastructure provisioning, struggling to manage complex deployments across environments, or facing unexpected downtime due to infrastructure issues then this book is meant for you. Experience with Microsoft Azure, Jenkins, shell scripting, and DevOps practices is required to get the most out of this Terraform book.
Terraform Cookbook: Recipes for Codifying Infrastructure
by Kerim Satirli Taylor DolezalCloud services and SaaS software permeate every company's IT landscape, requiring a shift from manually provisioned services to a more structured approach, with codification at its core. Terraform provides tools to manage the lifecycle of your IT landscape across thousands of different cloud providers and SaaS platforms.By defining your infrastructure as code you can safely and predictably make changes, modularize crucial building blocks, and create reusable service components. Each recipe in this cookbook addresses a specific problem and prefaces the solution with detailed insights into the "how" and "why".If you're just starting with Terraform and codified infrastructure, this book will help you create a solid foundation, on which you can build for years to come. If you're an advanced user, this guide will help you reaffirm your knowledge and take it to the next level, as you challenge yourself with more complex infrastructure, spread across multiple providers.Recipes include:Strategies on how to use Terraform with Version Control SystemsValidation and testing patterns for Terraform-managed infrastructureMethods for importing pre-existing resourcesTransforming infrastructure services into reusable componentsIntegrating Terraform with other HashiCorp toolsDeploying Containerized Workloads
Terraform Made Easy: Provisioning, Managing and Automating Cloud Infrastructure with Terraform on Google Cloud
by Ivy WangExplore the transformative benefits of Infrastructure as Code (IaC) and understand why Terraform is the go-to tool for managing cloud infrastructure efficiently. This book is your ultimate guide to mastering Terraform on Google Cloud Platform, providing you with the tools and knowledge to automate and optimize your cloud infrastructure with confidence. You’ll start by reviewing the traditional approach to managing infrastructure, common challenges, and the benefits of adopting IaC and Terraform. You’ll then learn how to install Terraform on various operating systems and get familiar with its configuration language, basic commands, and syntax. The book then turns to provisioning infrastructures on GCP, managing secrets and enhancing security, and concludes with integrating collaboration and DevOps using Terraform. The power of cloud platforms is growing, providing numerous ways to manage infrastructures more efficiently. While the traditional approach to infrastructure management works well on a smaller scale, it becomes a challenge when dealing with complex or extensive projects. From installation and configuration to advanced provisioning and security practices, this book provides a clear, step-by-step approach to mastering Terraform. What You Will Learn Explore providers, variables, modules, state management, and dependencies. Master encryption methods and IAM policies. Secure remote state management to protect sensitive data and ensure compliance. Discover frameworks, tools, and best practices for testing IaC code. Automate provisioning with CI/CD pipelines. Provision a comprehensive suite of infrastructure resources on Google Cloud Platform. Who This Book Is For Cloud engineers and architects, admin engineers, and CTOs familiar with programming languages and basic IT applications.
Terraform for Google Cloud Essential Guide: Learn how to provision infrastructure in Google Cloud securely and efficiently
by Bernd NordhausenBecome an expert in Terraform on Google Cloud by using Infrastructure as Code for provisioning multiple yet consistent environments to increase productivity in no timeKey FeaturesGet up and running with Terraform on Google CloudLearn Terraform concepts using Google Cloud code examplesApply Terraform to deploy realistic multi-tiered architectures quickly and repeatedlyBook DescriptionGoogle Cloud has adopted Terraform as the standard Infrastructure as Code tool. This necessitates a solid understanding of Terraform for any cloud architect or engineer working on Google Cloud. Yet no specific resources are available that focus on how to use Terraform on Google Cloud. This is the first book that teaches Terraform specifically for Google Cloud. You will take a journey from the basic concepts through to deploying complex architectures using Terraform. Using extensive code examples, you will receive guidance on how to authenticate Terraform in Google Cloud. As you advance, you'll get to grips with all the essential concepts of the Terraform language as applied to Google Cloud and deploy complete working architectures at the push of a button. Finally, you'll also be able to improve your Terraform workflow using Google Cloud native and third-party tools. By the end of this Terraform book, you will have gained a thorough understanding of Terraform and how to use it on Google Cloud, and be able to develop effective Terraform code, build reusable code, and utilize public domain Terraform modules to deploy on Google Cloud faster and more securely.What you will learnAuthenticate Terraform in Google Cloud using multiple methodsWrite efficient Terraform codeUse modules to share Terraform templatesManage multiple environments in Google CloudApply Terraform to deploy multi-tiered architecturesUse public modules to deploy complex architectures quicklyIntegrate Terraform into your Google Cloud environmentWho this book is forThis book is for Google Cloud architects and engineers who want to increase their productivity by using Terraform to automate the provisioning of Google Cloud deployments. A basic understanding of Google Cloud, such as the ability to provision resources using the Google Cloud console and using Cloud Shell, is assumed. Certification in Google Cloud is not required but helpful.
Terraform in Action (In Action Ser.)
by Scott WinklerTerraform in Action shows you how to automate and scale infrastructure programmatically using the Terraform toolkit.Summary In Terraform in Action you will learn: Cloud architecture with Terraform Terraform module sharing and the private module registry Terraform security in a multitenant environment Strategies for performing blue/green deployments Refactoring for code maintenance and reusability Running Terraform at scale Creating your own Terraform provider Using Terraform as a continuous development/continuous delivery platform Terraform in Action introduces the infrastructure-as-code (IaC) model that lets you instantaneously create new components and respond efficiently to changes in demand. You&’ll use the Terraform automation tool to design and manage servers that can be provisioned, shared, changed, tested, and deployed with a single command. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Provision, deploy, scale, and clone your entire stack to the cloud at the touch of a button. In Terraform, you create a collection of simple declarative scripts that define and manage application infrastructure. This powerful infrastructure-as-code approach automates key tasks like versioning and testing for everything from low-level networking to cloud services. About the book Terraform in Action shows you how to automate and scale infrastructure programmatically using the Terraform toolkit. Using practical, relevant examples, you&’ll use Terraform to provision a Kubernetes cluster, deploy a multiplayer game, and configure other hands-on projects. As you progress to advanced techniques like zero-downtime deployments, you&’ll discover how to think in Terraform rather than just copying and pasting scripts. What's inside Cloud architecture with Terraform Terraform module sharing and the private module registry Terraform security in a multitenant environment Strategies for performing blue/green deployments About the reader For readers experienced with a major cloud platform such as AWS. Examples in JavaScript and Golang. About the author Scott Winkler is a DevOps engineer and a distinguished Terraform expert. He has spoken multiple times at HashiTalks and HashiConf, and was selected as a HashiCorp Ambassador and Core Contributor in 2020. Table of Contents PART 1 TERRAFORM BOOTCAMP 1 Getting started with Terraform 2 Life cycle of a Terraform resource 3 Functional programming 4 Deploying a multi-tiered web application in AWS PART 2 TERRAFORM IN THE WILD 5 Serverless made easy 6 Terraform with friends 7 CI/CD pipelines as code 8 A multi-cloud MMORPG PART 3 MASTERING TERRAFORM 9 Zero-downtime deployments 10 Testing and refactoring 11 Extending Terraform by writing a custom provider 12 Automating Terraform 13 Security and secrets management
Terraform in Depth: Infrastructure as Code with Terraform and OpenTofu
by Robert HafnerAn in-depth guide to everything Terraform, complete with newly established best practices and experienced insights into Infrastructure as Code.Terraform and its open-source fork OpenTofu&’s &“Infrastructure as Code (IaC)&” approach has redefined the way you manage your infrastructure. Its premise is simple-yet-awesome: provision, update, scale, and replicate your infrastructure with the same ease as your application code. In Terraform in Depth, you&’ll discover absolutely everything you need to automate and manage your infrastructure with just a few lines of code. Inside Terraform in Depth, you&’ll learn how to: • Understand and write basic Terraform code • Avoid vendor lock-in with the open source OpenTofu • Switch between OpenTofu and Terraform as needed • Construct continuous integration and continuous delivery (CI/CD) pipelines for Terraform • Organize Terraform projects and modules for team-based, production use • Develop and test robust Terraform modules • Create custom Terraform providers Terraform in Depth is fully up to date with the latest versions, standards, and approaches of Terraform and OpenTofu. Complete and comprehensive, its one-stop approach covers everything from Terraform and OpenTofu&’s absolute basics all the way to advanced production uses. Every technique is illustrated with the kind of real-world examples infrastructure engineers encounter every day. Forewords by Anton Babenko and Christian Mesh. About the technology Terraform and its open-source fork OpenTofu practically eliminate manual infrastructure configuration. With the Terraform infrastructure management tool, even complex operations that used to require kludgy scripts and time-sucking tinkering can be created, managed, and shared as an organized codebase. Master Terraform, and you&’ll be able to update a fleet of machines with just a few lines of code. About the book Terraform in Depth teaches Terraform techniques and Infrastructure as Code (IaC) practices that you can use to deploy and manage applications in the cloud or your on-prem data center. Each chapter includes interesting hands-on examples, such as creating a flexible Terraform module and debugging Terraform plans. You&’ll quickly learn to define your infrastructure with Terraform. Then, you&’ll dive into advanced applications, including CI/CD pipelines, creating tools for documentation and security, and Terraform code management. What's inside • Understand and write basic Terraform code • Avoid vendor lock-in with OpenTofu • Construct CI/CD pipelines • Develop and test Terraform modules About the reader For sysadmins, software developers, and cloud engineers famil- iar with the CLI. About the author Robert Hafner has led engineering efforts at numerous startups, including Malwarebytes, Vicarious AI, and Rad AI. He is currently a Distinguished Engineer at a Fortune 100 Telecom. Table of Contents Part 1 1 A brief overview of Terraform 2 Terraform HCL components 3 Terraform variables and modules 4 Expressions and iterations 5 The Terraform plan Part 2 6 State management 7 Code quality and continuous integration 8 Continuous delivery and deployment 9 Testing and refactoring Part 3 10 Advanced Terraform topics 11 Alternative interfaces 12 Terraform providers
Terraform: Writing Infrastructure as Code
by Yevgeniy BrikmanTerraform has emerged as a key player in the DevOps world for defining, launching, and managing infrastructure as code (IAC) across a variety of cloud and virtualization platforms, including AWS, Google Cloud, and Azure. This hands-on book is the fastest way to get up and running with Terraform.Gruntwork co-founder Yevgeniy (Jim) Brikman walks you through dozens of code examples that demonstrate how to use Terraform’s simple, declarative programming language to deploy and manage infrastructure with just a few commands. Whether you’re a novice developer, aspiring DevOps engineer, or veteran sysadmin, this book will take you from Terraform basics to running a full tech stack capable of supporting a massive amount of traffic and a large team of developers.Compare Terraform to other IAC tools, such as Chef, Puppet, Ansible, and Salt StackUse Terraform to deploy server clusters, load balancers, and databasesLearn how Terraform manages the state of your infrastructure and how it impacts file layout, isolation, and lockingCreate reusable infrastructure with Terraform modulesTry out advanced Terraform syntax to implement loops, if-statements, and zero-downtime deploymentUse Terraform as a team, including best practices for writing, testing, and versioning Terraform code
Terraform: Writing Infrastructure as Code
by Yevgeniy BrikmanTerraform has become a key player in the DevOps world for defining, launching, and managing infrastructure as code (IaC) across a variety of cloud and virtualization platforms, including AWS, Google Cloud, Azure, and more. This hands-on second edition, expanded and thoroughly updated for Terraform version 0.12 and beyond, shows you the fastest way to get up and running.Gruntwork cofounder Yevgeniy (Jim) Brikman walks you through code examples that demonstrate Terraform’s simple, declarative programming language for deploying and managing infrastructure with a few commands. Veteran sysadmins, DevOps engineers, and novice developers will quickly go from Terraform basics to running a full stack that can support a massive amount of traffic and a large team of developers.Explore changes from Terraform 0.9 through 0.12, including backends, workspaces, and first-class expressionsLearn how to write production-grade Terraform modulesDive into manual and automated testing for Terraform codeCompare Terraform to Chef, Puppet, Ansible, CloudFormation, and Salt StackDeploy server clusters, load balancers, and databasesUse Terraform to manage the state of your infrastructureCreate reusable infrastructure with Terraform modulesUse advanced Terraform syntax to achieve zero-downtime deployment
Terraform: Writing Infrastructure as Code
by Yevgeniy BrikmanTerraform has become a key player in the DevOps world for defining, launching, and managing infrastructure as code (IaC) across a variety of cloud and virtualization platforms, including AWS, Google Cloud, Azure, and more. This hands-on third edition, expanded and thoroughly updated for version 1.0 and beyond, shows you the fastest way to get up and running with Terraform.Gruntwork cofounder Yevgeniy (Jim) Brikman takes you through code examples that demonstrate Terraform's simple, declarative programming language for deploying and managing infrastructure with a few commands. Veteran sysadmins, DevOps engineers, and novice developers will quickly go from Terraform basics to running a full stack that can support a massive amount of traffic and a large team of developers.Compare Terraform with Chef, Puppet, Ansible, CloudFormation, and PulumiDeploy servers, load balancers, and databasesCreate reusable infrastructure with Terraform modulesTest your Terraform modules with static analysis, unit tests, and integration testsConfigure CI/CD pipelines for both your apps and infrastructure codeUse advanced Terraform syntax for loops, conditionals, and zero-downtime deploymentGet up to speed on Terraform 0.13 to 1.0 and beyondWork with multiple clouds and providers (including Kubernetes!)
Terrestrische Methoden (Grundlagen der Physikalischen und Mathematischen Geodäsie)
by Karl Heinz IlkDieses Lehrbuch aus der Reihe „Grundlagen der Physikalischen und Mathematischen Geodäsie“ widmet sich den terrestrischen Verfahren der Physikalischen Geodäsie. Der Autor schlägt eine Brücke von den klassischen Verfahren der Erdmessung zu den modernen Methoden. Dafür wird eine kurze überblicksartige Zusammenfassung der historischen Entwicklung der Bestimmung der Erdfigur bis zu den ersten Ansätzen eines dynamischen Erdmodells gegeben. Es folgt eine Erläuterung der Bestimmung von Figur und Schwerefeld der Erde mit Hilfe der Lösung einer freien Randwertaufgabe nach Stokes und Molodensky. Darauf aufbauend werden die verschiedenen Aspekte der Geoidberechnung behandelt. Dann stellt der Autor den modernen Ansatz, Figur und Schwerefeld der Erde als Approximationsproblem zu lösen, ausführlich dar – beginnend von Interpolationsansätzen über die Gaußsche Fehlerquadratmethode bis zur sog. Kollokation nach kleinsten Quadraten.