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Author: Cybellium Ltd Publisher: Cybellium Ltd ISBN: Category : Computers Languages : en Pages : 193
Book Description
Cybellium Ltd is dedicated to empowering individuals and organizations with the knowledge and skills they need to navigate the ever-evolving computer science landscape securely and learn only the latest information available on any subject in the category of computer science including: - Information Technology (IT) - Cyber Security - Information Security - Big Data - Artificial Intelligence (AI) - Engineering - Robotics - Standards and compliance Our mission is to be at the forefront of computer science education, offering a wide and comprehensive range of resources, including books, courses, classes and training programs, tailored to meet the diverse needs of any subject in computer science. Visit https://www.cybellium.com for more books.
Author: Cybellium Ltd Publisher: Cybellium Ltd ISBN: Category : Computers Languages : en Pages : 205
Book Description
Cybellium Ltd is dedicated to empowering individuals and organizations with the knowledge and skills they need to navigate the ever-evolving computer science landscape securely and learn only the latest information available on any subject in the category of computer science including: - Information Technology (IT) - Cyber Security - Information Security - Big Data - Artificial Intelligence (AI) - Engineering - Robotics - Standards and compliance Our mission is to be at the forefront of computer science education, offering a wide and comprehensive range of resources, including books, courses, classes and training programs, tailored to meet the diverse needs of any subject in computer science. Visit https://www.cybellium.com for more books.
Author: Rajkumar Buyya Publisher: Newnes ISBN: 0124095399 Category : Computers Languages : en Pages : 469
Book Description
Mastering Cloud Computing is designed for undergraduate students learning to develop cloud computing applications. Tomorrow's applications won't live on a single computer but will be deployed from and reside on a virtual server, accessible anywhere, any time. Tomorrow's application developers need to understand the requirements of building apps for these virtual systems, including concurrent programming, high-performance computing, and data-intensive systems. The book introduces the principles of distributed and parallel computing underlying cloud architectures and specifically focuses on virtualization, thread programming, task programming, and map-reduce programming. There are examples demonstrating all of these and more, with exercises and labs throughout. - Explains how to make design choices and tradeoffs to consider when building applications to run in a virtual cloud environment - Real-world case studies include scientific, business, and energy-efficiency considerations
Author: Mohsin Shafique Hijazee Publisher: Packt Publishing Ltd ISBN: 1784394920 Category : Computers Languages : en Pages : 368
Book Description
Build robust and highly scalable web applications with Google App Engine About This Book Get an in-depth look at how Google App Engine works under the hood Design and model your application around Google's highly scalable distributed NoSQL datastore to unlock its full potential A comprehensive guide to ensure your mastery of Google App Engine Who This Book Is For If you have been developing web applications in Python or any other dynamic language but have always wondered how to write highly scalable web applications without getting into system administration and other plumbing, then this is the book for you. No experience in writing scalable applications is required. What You Will Learn Scale and develop your applications with Google App Engine's runtime environment Get to grips with request handling mechanism and write request handlers Deep dive into Google's distributed NoSQL and highly scalable datastore and design your application around it Implement powerful search with scalable datastore Perform long-running tasks in the background using task queues Write compartmentalized apps using multi tenancy, memcache, and other Google App Engine runtime services Handle web requests using the CGI, WSGI, and multi-threaded configurations Deploy, tweak, and manage apps in production on Google App Engine In Detail Developing web applications that serve millions of users is no easy task, as it involves a number of configurations and administrative tasks for the underlying software and hardware stack. This whole configuration requires not only expertise, but also a fair amount of time as well. Time that could have been spent on actual application functionality. Google App Engine allows you develop highly scalable web applications or backends for mobile applications without worrying about the system administration plumbing or hardware provisioning issues. Just focus writing on your business logic, the meat of the application, and let Google's powerful infrastructure scale it to thousands of requests per second and millions of users without any effort on your part. This book takes you from explaining how scalable applications work to designing and developing robust scalable web applications of your own, utilizing services available on Google App Engine. Starting with a walkthrough of scalability is and how scalable web applications work, this book introduces you to the environment under which your applications exist on Google App Engine. Next, you will learn about Google's datastore, which is a massively scalable distributed NoSQL solution built on top of BigTable. You will examine the BigTable concepts and operations in detail and reveal how it is used to build Google datastore. Armed with this knowledge, you will then advance towards how to best model your data and query that along with transactions. To augment the powerful distributed dataset, you will deep dive into search functionality offered on Google App Engine. With the search and storage sorted out, you will get a look into performing long running tasks in the background using Google App Engine task queues along with sending and receiving emails. You will also examine the memcache to boost web application performance, image processing for common image manipulation tasks. You will then explore uploading, storing, and serving large files using Blobstore and Cloud storage. Finally, you will be presented with the deployment and monitoring of your applications in production along with a detailed look at dividing applications into different working modules. Style and approach This book is an in-depth guide where you will examine the problems in the context of highly scalable web applications. This book will take you through the libraries, services, and required configuration and finally puts everything together into a small web application that showcases all the capabilities of Google App Engine.
Author: Peter Jones Publisher: Walzone Press ISBN: Category : Computers Languages : en Pages : 210
Book Description
Explore the power of automating cloud infrastructure with our comprehensive guide to Google Cloud Deployment Manager. Whether you're a cloud professional, DevOps engineer, or system administrator navigating the complexities of cloud infrastructures, this book is tailored to advance your skills in leveraging Google Cloud's potent tool for orchestrating cloud resources effectively. "Streamlining Cloud Infrastructure: Mastering Google Cloud Deployment Manager" unfolds the secrets to designing, deploying, and managing scalable and secure cloud resources with precision. From understanding the fundamentals to mastering advanced techniques, each chapter is meticulously crafted to provide in-depth coverage and practical insights into managing infrastructure as code, ensuring operational efficiency, and optimizing costs. Delve into the essentials of resource and configuration management, learn the art of designing and templating your infrastructure, and unlock advanced deployment strategies to tackle complex scenarios. Gain expertise in securing deployments, integrating with Google Cloud Services, and monitoring your cloud environment to maintain peak performance. With a direct and professional approach, this book offers a wealth of knowledge, best practices, and expert tips for transforming your cloud deployment processes. Whether you're looking to enhance your existing skills or embark on automating cloud deployments for the first time, "Streamlining Cloud Infrastructure: Mastering Google Cloud Deployment Manager" is your go-to resource for mastering cloud infrastructure automation with confidence and efficiency. Embrace the future of cloud computing and elevate your cloud management capabilities to new heights.
Author: Andrew Morgan Publisher: Packt Publishing Ltd ISBN: 1785888285 Category : Computers Languages : en Pages : 550
Book Description
Master the techniques and sophisticated analytics used to construct Spark-based solutions that scale to deliver production-grade data science products About This Book Develop and apply advanced analytical techniques with Spark Learn how to tell a compelling story with data science using Spark's ecosystem Explore data at scale and work with cutting edge data science methods Who This Book Is For This book is for those who have beginner-level familiarity with the Spark architecture and data science applications, especially those who are looking for a challenge and want to learn cutting edge techniques. This book assumes working knowledge of data science, common machine learning methods, and popular data science tools, and assumes you have previously run proof of concept studies and built prototypes. What You Will Learn Learn the design patterns that integrate Spark into industrialized data science pipelines See how commercial data scientists design scalable code and reusable code for data science services Explore cutting edge data science methods so that you can study trends and causality Discover advanced programming techniques using RDD and the DataFrame and Dataset APIs Find out how Spark can be used as a universal ingestion engine tool and as a web scraper Practice the implementation of advanced topics in graph processing, such as community detection and contact chaining Get to know the best practices when performing Extended Exploratory Data Analysis, commonly used in commercial data science teams Study advanced Spark concepts, solution design patterns, and integration architectures Demonstrate powerful data science pipelines In Detail Data science seeks to transform the world using data, and this is typically achieved through disrupting and changing real processes in real industries. In order to operate at this level you need to build data science solutions of substance –solutions that solve real problems. Spark has emerged as the big data platform of choice for data scientists due to its speed, scalability, and easy-to-use APIs. This book deep dives into using Spark to deliver production-grade data science solutions. This process is demonstrated by exploring the construction of a sophisticated global news analysis service that uses Spark to generate continuous geopolitical and current affairs insights.You will learn all about the core Spark APIs and take a comprehensive tour of advanced libraries, including Spark SQL, Spark Streaming, MLlib, and more. You will be introduced to advanced techniques and methods that will help you to construct commercial-grade data products. Focusing on a sequence of tutorials that deliver a working news intelligence service, you will learn about advanced Spark architectures, how to work with geographic data in Spark, and how to tune Spark algorithms so they scale linearly. Style and approach This is an advanced guide for those with beginner-level familiarity with the Spark architecture and working with Data Science applications. Mastering Spark for Data Science is a practical tutorial that uses core Spark APIs and takes a deep dive into advanced libraries including: Spark SQL, visual streaming, and MLlib. This book expands on titles like: Machine Learning with Spark and Learning Spark. It is the next learning curve for those comfortable with Spark and looking to improve their skills.
Author: Gergely Daroczi Publisher: Packt Publishing Ltd ISBN: 1783982039 Category : Computers Languages : en Pages : 397
Book Description
Gain sharp insights into your data and solve real-world data science problems with R—from data munging to modeling and visualization About This Book Handle your data with precision and care for optimal business intelligence Restructure and transform your data to inform decision-making Packed with practical advice and tips to help you get to grips with data mining Who This Book Is For If you are a data scientist or R developer who wants to explore and optimize your use of R's advanced features and tools, this is the book for you. A basic knowledge of R is required, along with an understanding of database logic. What You Will Learn Connect to and load data from R's range of powerful databases Successfully fetch and parse structured and unstructured data Transform and restructure your data with efficient R packages Define and build complex statistical models with glm Develop and train machine learning algorithms Visualize social networks and graph data Deploy supervised and unsupervised classification algorithms Discover how to visualize spatial data with R In Detail R is an essential language for sharp and successful data analysis. Its numerous features and ease of use make it a powerful way of mining, managing, and interpreting large sets of data. In a world where understanding big data has become key, by mastering R you will be able to deal with your data effectively and efficiently. This book will give you the guidance you need to build and develop your knowledge and expertise. Bridging the gap between theory and practice, this book will help you to understand and use data for a competitive advantage. Beginning with taking you through essential data mining and management tasks such as munging, fetching, cleaning, and restructuring, the book then explores different model designs and the core components of effective analysis. You will then discover how to optimize your use of machine learning algorithms for classification and recommendation systems beside the traditional and more recent statistical methods. Style and approach Covering the essential tasks and skills within data science, Mastering Data Analysis provides you with solutions to the challenges of data science. Each section gives you a theoretical overview before demonstrating how to put the theory to work with real-world use cases and hands-on examples.
Author: Cybellium Ltd
Author: Cybellium Ltd
Author: Cybellium Ltd
Author: Cybellium Ltd
Author: Rajkumar Buyya
Author: Mohsin Shafique Hijazee
Author: Peter Jones
Author: Cybellium Ltd
Author: Andrew Morgan
Author: Cybellium Ltd
Author: Gergely Daroczi