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Author: Trâm Ngọc Phạm
Publisher: Packt Publishing Ltd
ISBN: 1805126857
Category : Computers
Languages : en
Pages : 529
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Book Description
Master AWS data engineering services and techniques for orchestrating pipelines, building layers, and managing migrations Key Features Get up to speed with the different AWS technologies for data engineering Learn the different aspects and considerations of building data lakes, such as security, storage, and operations Get hands on with key AWS services such as Glue, EMR, Redshift, QuickSight, and Athena for practical learning Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionPerforming data engineering with Amazon Web Services (AWS) combines AWS's scalable infrastructure with robust data processing tools, enabling efficient data pipelines and analytics workflows. This comprehensive guide to AWS data engineering will teach you all you need to know about data lake management, pipeline orchestration, and serving layer construction. Through clear explanations and hands-on exercises, you’ll master essential AWS services such as Glue, EMR, Redshift, QuickSight, and Athena. Additionally, you’ll explore various data platform topics such as data governance, data quality, DevOps, CI/CD, planning and performing data migration, and creating Infrastructure as Code. As you progress, you will gain insights into how to enrich your platform and use various AWS cloud services such as AWS EventBridge, AWS DataZone, and AWS SCT and DMS to solve data platform challenges. Each recipe in this book is tailored to a daily challenge that a data engineer team faces while building a cloud platform. By the end of this book, you will be well-versed in AWS data engineering and have gained proficiency in key AWS services and data processing techniques. You will develop the necessary skills to tackle large-scale data challenges with confidence.What you will learn Define your centralized data lake solution, and secure and operate it at scale Identify the most suitable AWS solution for your specific needs Build data pipelines using multiple ETL technologies Discover how to handle data orchestration and governance Explore how to build a high-performing data serving layer Delve into DevOps and data quality best practices Migrate your data from on-premises to AWS Who this book is for If you're involved in designing, building, or overseeing data solutions on AWS, this book provides proven strategies for addressing challenges in large-scale data environments. Data engineers as well as big data professionals looking to enhance their understanding of AWS features for optimizing their workflow, even if they're new to the platform, will find value. Basic familiarity with AWS security (users and roles) and command shell is recommended.
Author: Trâm Ngọc Phạm
Publisher: Packt Publishing Ltd
ISBN: 1805126857
Category : Computers
Languages : en
Pages : 529
Get Book Here
Book Description
Master AWS data engineering services and techniques for orchestrating pipelines, building layers, and managing migrations Key Features Get up to speed with the different AWS technologies for data engineering Learn the different aspects and considerations of building data lakes, such as security, storage, and operations Get hands on with key AWS services such as Glue, EMR, Redshift, QuickSight, and Athena for practical learning Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionPerforming data engineering with Amazon Web Services (AWS) combines AWS's scalable infrastructure with robust data processing tools, enabling efficient data pipelines and analytics workflows. This comprehensive guide to AWS data engineering will teach you all you need to know about data lake management, pipeline orchestration, and serving layer construction. Through clear explanations and hands-on exercises, you’ll master essential AWS services such as Glue, EMR, Redshift, QuickSight, and Athena. Additionally, you’ll explore various data platform topics such as data governance, data quality, DevOps, CI/CD, planning and performing data migration, and creating Infrastructure as Code. As you progress, you will gain insights into how to enrich your platform and use various AWS cloud services such as AWS EventBridge, AWS DataZone, and AWS SCT and DMS to solve data platform challenges. Each recipe in this book is tailored to a daily challenge that a data engineer team faces while building a cloud platform. By the end of this book, you will be well-versed in AWS data engineering and have gained proficiency in key AWS services and data processing techniques. You will develop the necessary skills to tackle large-scale data challenges with confidence.What you will learn Define your centralized data lake solution, and secure and operate it at scale Identify the most suitable AWS solution for your specific needs Build data pipelines using multiple ETL technologies Discover how to handle data orchestration and governance Explore how to build a high-performing data serving layer Delve into DevOps and data quality best practices Migrate your data from on-premises to AWS Who this book is for If you're involved in designing, building, or overseeing data solutions on AWS, this book provides proven strategies for addressing challenges in large-scale data environments. Data engineers as well as big data professionals looking to enhance their understanding of AWS features for optimizing their workflow, even if they're new to the platform, will find value. Basic familiarity with AWS security (users and roles) and command shell is recommended.
Author: Abhishek Mishra
Publisher: John Wiley & Sons
ISBN: 1119556732
Category : Computers
Languages : en
Pages : 531
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Book Description
Put the power of AWS Cloud machine learning services to work in your business and commercial applications! Machine Learning in the AWS Cloud introduces readers to the machine learning (ML) capabilities of the Amazon Web Services ecosystem and provides practical examples to solve real-world regression and classification problems. While readers do not need prior ML experience, they are expected to have some knowledge of Python and a basic knowledge of Amazon Web Services. Part One introduces readers to fundamental machine learning concepts. You will learn about the types of ML systems, how they are used, and challenges you may face with ML solutions. Part Two focuses on machine learning services provided by Amazon Web Services. You’ll be introduced to the basics of cloud computing and AWS offerings in the cloud-based machine learning space. Then you’ll learn to use Amazon Machine Learning to solve a simpler class of machine learning problems, and Amazon SageMaker to solve more complex problems. • Learn techniques that allow you to preprocess data, basic feature engineering, visualizing data, and model building • Discover common neural network frameworks with Amazon SageMaker • Solve computer vision problems with Amazon Rekognition • Benefit from illustrations, source code examples, and sidebars in each chapter The book appeals to both Python developers and technical/solution architects. Developers will find concrete examples that show them how to perform common ML tasks with Python on AWS. Technical/solution architects will find useful information on the machine learning capabilities of the AWS ecosystem.
Author: Rajdeep Dua
Publisher: Packt Publishing Ltd
ISBN: 1785886428
Category : Computers
Languages : en
Pages : 523
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Book Description
Create scalable machine learning applications to power a modern data-driven business using Spark 2.x About This Book Get to the grips with the latest version of Apache Spark Utilize Spark's machine learning library to implement predictive analytics Leverage Spark's powerful tools to load, analyze, clean, and transform your data Who This Book Is For If you have a basic knowledge of machine learning and want to implement various machine-learning concepts in the context of Spark ML, this book is for you. You should be well versed with the Scala and Python languages. What You Will Learn Get hands-on with the latest version of Spark ML Create your first Spark program with Scala and Python Set up and configure a development environment for Spark on your own computer, as well as on Amazon EC2 Access public machine learning datasets and use Spark to load, process, clean, and transform data Use Spark's machine learning library to implement programs by utilizing well-known machine learning models Deal with large-scale text data, including feature extraction and using text data as input to your machine learning models Write Spark functions to evaluate the performance of your machine learning models In Detail This book will teach you about popular machine learning algorithms and their implementation. You will learn how various machine learning concepts are implemented in the context of Spark ML. You will start by installing Spark in a single and multinode cluster. Next you'll see how to execute Scala and Python based programs for Spark ML. Then we will take a few datasets and go deeper into clustering, classification, and regression. Toward the end, we will also cover text processing using Spark ML. Once you have learned the concepts, they can be applied to implement algorithms in either green-field implementations or to migrate existing systems to this new platform. You can migrate from Mahout or Scikit to use Spark ML. By the end of this book, you will acquire the skills to leverage Spark's features to create your own scalable machine learning applications and power a modern data-driven business. Style and approach This practical tutorial with real-world use cases enables you to develop your own machine learning systems with Spark. The examples will help you combine various techniques and models into an intelligent machine learning system.
Author: Sonali Sahu
Publisher: Packt Publishing Ltd
ISBN: 1803233532
Category : Computers
Languages : en
Pages : 246
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Book Description
Build real-world artificial intelligence applications across industries with the help of intelligent document processing Key FeaturesTackle common document processing problems to extract value from any type of documentUnlock deeper levels of insights on IDP in a more structured and accelerated way using AWS AI/MLApply your knowledge to solve real document analysis problems in various industry applicationsBook Description With the volume of data growing exponentially in this digital era, it has become paramount for professionals to process this data in an accelerated and cost-effective manner to get value out of it. Data that organizations receive is usually in raw document format, and being able to process these documents is critical to meeting growing business needs. This book is a comprehensive guide to helping you get to grips with AI/ML fundamentals and their application in document processing use cases. You'll begin by understanding the challenges faced in legacy document processing and discover how you can build end-to-end document processing pipelines with AWS AI services. As you advance, you'll get hands-on experience with popular Python libraries to process and extract insights from documents. This book starts with the basics, taking you through real industry use cases for document processing to deliver value-based care in the healthcare industry and accelerate loan application processing in the financial industry. Throughout the chapters, you'll find out how to apply your skillset to solve practical problems. By the end of this AWS book, you'll have mastered the fundamentals of document processing with machine learning through practical implementation. What you will learnUnderstand the requirements and challenges in deriving insights from a documentExplore common stages in the intelligent document processing pipelineDiscover how AWS AI/ML can successfully automate IDP pipelinesFind out how to write clean and elegant Python code by leveraging AIGet to grips with the concepts and functionalities of AWS AI servicesExplore IDP across industries such as insurance, healthcare, finance, and the public sectorDetermine how to apply business rules in IDPBuild, train, and deploy models with serverless architecture for IDPWho this book is for This book is for technical professionals and thought leaders who want to understand and solve business problems by leveraging insights from their documents. If you want to learn about machine learning and artificial intelligence, and work with real-world use cases such as document processing with technology, this book is for you. To make the most of this book, you should have basic knowledge of AI/ML and python programming concepts. This book is also especially useful for developers looking to explore AI/ML with industry use cases.
Author: Michael Dooley
Publisher: Simon and Schuster
ISBN: 162153586X
Category : Art
Languages : en
Pages : 364
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Book Description
Featuring essays by, and interviews with, more than sixty professionals, educators, and critics, the book provides an in-depth view of the art, business, and history of comics art. Readers will learn about a wide variety of genres, from editorial cartoons, political comics, and comic strips to graphic novels, superhero sagas, and alternative comics. Other featured topics include the role of comic art in related fields such as animation, design, and illustration; lesson plans by top teachers; and essays on how to thrive and grow as a creative comic artist.
Author: Noah Gift
Publisher: "O'Reilly Media, Inc."
ISBN: 1492057649
Category : Computers
Languages : en
Pages : 506
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Book Description
Much has changed in technology over the past decade. Data is hot, the cloud is ubiquitous, and many organizations need some form of automation. Throughout these transformations, Python has become one of the most popular languages in the world. This practical resource shows you how to use Python for everyday Linux systems administration tasks with today’s most useful DevOps tools, including Docker, Kubernetes, and Terraform. Learning how to interact and automate with Linux is essential for millions of professionals. Python makes it much easier. With this book, you’ll learn how to develop software and solve problems using containers, as well as how to monitor, instrument, load-test, and operationalize your software. Looking for effective ways to "get stuff done" in Python? This is your guide. Python foundations, including a brief introduction to the language How to automate text, write command-line tools, and automate the filesystem Linux utilities, package management, build systems, monitoring and instrumentation, and automated testing Cloud computing, infrastructure as code, Kubernetes, and serverless Machine learning operations and data engineering from a DevOps perspective Building, deploying, and operationalizing a machine learning project
Author: Vijayalakshmi Saravanan
Publisher: CRC Press
ISBN: 100025853X
Category : Technology & Engineering
Languages : en
Pages : 187
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Book Description
This book covers IoT and Big Data from a technical and business point of view. The book explains the design principles, algorithms, technical knowledge, and marketing for IoT systems. It emphasizes applications of big data and IoT. It includes scientific algorithms and key techniques for fusion of both areas. Real case applications from different industries are offering to facilitate ease of understanding the approach. The book goes on to address the significance of security algorithms in combing IoT and big data which is currently evolving in communication technologies. The book is written for researchers, professionals, and academicians from interdisciplinary and transdisciplinary areas. The readers will get an opportunity to know the conceptual ideas with step-by-step pragmatic examples which makes ease of understanding no matter the level of the reader.
Author: James D. White
Publisher: Harvard Business Press
ISBN: 1647821983
Category : Business & Economics
Languages : en
Pages : 124
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Book Description
Building anti-racist companies by design creates great places to work for all. Business leaders ready to take a bold stance to make the world better for employees, for consumers, and for the greater community: Read this book. As leaders, you have the unique ability to reach thousands of employees and millions of consumers. It's time for you to build a truly diverse, equitable, and inclusive work environment and, by extension, a more just society. This book provides a comprehensive plan for leaders who are ready to get serious about diversity, equity, and inclusion (DEI) and to create an anti-racist company culture. As a Black man at the highest levels of corporate America for over thirty years, James D. White has built a deep understanding of how to operationalize and integrate DEI agendas. As CEO and Chairman of the global smoothie chain Jamba Juice, he led a remarkable turnaround to make the company a model of strong performance built on a foundation of a diverse, anti-racist culture. He also draws on the experiences of other leaders at the vanguard of DEI. White writes with his daughter, Krista White, who brings to this book the heart and sensibilities of a younger generation devoted to equity and inclusion and intent on justice. Practical lessons and real-world examples of techniques used by seasoned experts will empower leaders who, at this urgent moment, are asking themselves what so many have asked James White: What can I do? You can start by reading this book.
Author: Chris Peiris
Publisher: John Wiley & Sons
ISBN: 1119804108
Category : Computers
Languages : en
Pages : 636
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Book Description
Implement a vendor-neutral and multi-cloud cybersecurity and risk mitigation framework with advice from seasoned threat hunting pros In Threat Hunting in the Cloud: Defending AWS, Azure and Other Cloud Platforms Against Cyberattacks, celebrated cybersecurity professionals and authors Chris Peiris, Binil Pillai, and Abbas Kudrati leverage their decades of experience building large scale cyber fusion centers to deliver the ideal threat hunting resource for both business and technical audiences. You'll find insightful analyses of cloud platform security tools and, using the industry leading MITRE ATT&CK framework, discussions of the most common threat vectors. You'll discover how to build a side-by-side cybersecurity fusion center on both Microsoft Azure and Amazon Web Services and deliver a multi-cloud strategy for enterprise customers. And you will find out how to create a vendor-neutral environment with rapid disaster recovery capability for maximum risk mitigation. With this book you'll learn: Key business and technical drivers of cybersecurity threat hunting frameworks in today's technological environment Metrics available to assess threat hunting effectiveness regardless of an organization's size How threat hunting works with vendor-specific single cloud security offerings and on multi-cloud implementations A detailed analysis of key threat vectors such as email phishing, ransomware and nation state attacks Comprehensive AWS and Azure "how to" solutions through the lens of MITRE Threat Hunting Framework Tactics, Techniques and Procedures (TTPs) Azure and AWS risk mitigation strategies to combat key TTPs such as privilege escalation, credential theft, lateral movement, defend against command & control systems, and prevent data exfiltration Tools available on both the Azure and AWS cloud platforms which provide automated responses to attacks, and orchestrate preventative measures and recovery strategies Many critical components for successful adoption of multi-cloud threat hunting framework such as Threat Hunting Maturity Model, Zero Trust Computing, Human Elements of Threat Hunting, Integration of Threat Hunting with Security Operation Centers (SOCs) and Cyber Fusion Centers The Future of Threat Hunting with the advances in Artificial Intelligence, Machine Learning, Quantum Computing and the proliferation of IoT devices. Perfect for technical executives (i.e., CTO, CISO), technical managers, architects, system admins and consultants with hands-on responsibility for cloud platforms, Threat Hunting in the Cloud is also an indispensable guide for business executives (i.e., CFO, COO CEO, board members) and managers who need to understand their organization's cybersecurity risk framework and mitigation strategy.
Author: Kim Crawley
Publisher: Packt Publishing Ltd
ISBN: 1803248866
Category : Computers
Languages : en
Pages : 298
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Book Description
Get to grips with cloud exploits, learn the fundamentals of cloud security, and secure your organization's network by pentesting AWS, Azure, and GCP effectively Key Features Discover how enterprises use AWS, Azure, and GCP as well as the applications and services unique to each platform Understand the key principles of successful pentesting and its application to cloud networks, DevOps, and containerized networks (Docker and Kubernetes) Get acquainted with the penetration testing tools and security measures specific to each platform Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionWith AWS, Azure, and GCP gaining prominence, understanding their unique features, ecosystems, and penetration testing protocols has become an indispensable skill, which is precisely what this pentesting guide for cloud platforms will help you achieve. As you navigate through the chapters, you’ll explore the intricacies of cloud security testing and gain valuable insights into how pentesters evaluate cloud environments effectively. In addition to its coverage of these cloud platforms, the book also guides you through modern methodologies for testing containerization technologies such as Docker and Kubernetes, which are fast becoming staples in the cloud ecosystem. Additionally, it places extended focus on penetration testing AWS, Azure, and GCP through serverless applications and specialized tools. These sections will equip you with the tactics and tools necessary to exploit vulnerabilities specific to serverless architecture, thus providing a more rounded skill set. By the end of this cloud security book, you’ll not only have a comprehensive understanding of the standard approaches to cloud penetration testing but will also be proficient in identifying and mitigating vulnerabilities that are unique to cloud environments.What you will learn Familiarize yourself with the evolution of cloud networks Navigate and secure complex environments that use more than one cloud service Conduct vulnerability assessments to identify weak points in cloud configurations Secure your cloud infrastructure by learning about common cyber attack techniques Explore various strategies to successfully counter complex cloud attacks Delve into the most common AWS, Azure, and GCP services and their applications for businesses Understand the collaboration between red teamers, cloud administrators, and other stakeholders for cloud pentesting Who this book is for This book is for aspiring Penetration Testers, and the Penetration Testers seeking specialized skills for leading cloud platforms—AWS, Azure, and GCP. Those working in defensive security roles will also find this book useful to extend their cloud security skills.
