Accelerate Deep Learning Workloads With Amazon Sagemaker
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Accelerate Deep Learning Workloads With Amazon Sagemaker
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Author : Vadim Dabravolski
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-10-28
Accelerate Deep Learning Workloads With Amazon Sagemaker written by Vadim Dabravolski and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-28 with Computers categories.
Plan and design model serving infrastructure to run and troubleshoot distributed deep learning training jobs for improved model performance. Key FeaturesExplore key Amazon SageMaker capabilities in the context of deep learningTrain and deploy deep learning models using SageMaker managed capabilities and optimize your deep learning workloadsCover in detail the theoretical and practical aspects of training and hosting your deep learning models on Amazon SageMakerBook Description Over the past 10 years, deep learning has grown from being an academic research field to seeing wide-scale adoption across multiple industries. Deep learning models demonstrate excellent results on a wide range of practical tasks, underpinning emerging fields such as virtual assistants, autonomous driving, and robotics. In this book, you will learn about the practical aspects of designing, building, and optimizing deep learning workloads on Amazon SageMaker. The book also provides end-to-end implementation examples for popular deep-learning tasks, such as computer vision and natural language processing. You will begin by exploring key Amazon SageMaker capabilities in the context of deep learning. Then, you will explore in detail the theoretical and practical aspects of training and hosting your deep learning models on Amazon SageMaker. You will learn how to train and serve deep learning models using popular open-source frameworks and understand the hardware and software options available for you on Amazon SageMaker. The book also covers various optimizations technique to improve the performance and cost characteristics of your deep learning workloads. By the end of this book, you will be fluent in the software and hardware aspects of running deep learning workloads using Amazon SageMaker. What you will learnCover key capabilities of Amazon SageMaker relevant to deep learning workloadsOrganize SageMaker development environmentPrepare and manage datasets for deep learning trainingDesign, debug, and implement the efficient training of deep learning modelsDeploy, monitor, and optimize the serving of DL modelsWho this book is for This book is relevant for ML engineers who work on deep learning model development and training, and for Solutions Architects who design and optimize end-to-end deep learning workloads. It assumes familiarity with the Python ecosystem, principles of Machine Learning and Deep Learning, and basic knowledge of the AWS cloud.
Applied Machine Learning And High Performance Computing On Aws
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Author : Mani Khanuja
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-12-30
Applied Machine Learning And High Performance Computing On Aws written by Mani Khanuja and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-30 with Computers categories.
Build, train, and deploy large machine learning models at scale in various domains such as computational fluid dynamics, genomics, autonomous vehicles, and numerical optimization using Amazon SageMaker Key FeaturesUnderstand the need for high-performance computing (HPC)Build, train, and deploy large ML models with billions of parameters using Amazon SageMakerLearn best practices and architectures for implementing ML at scale using HPCBook Description Machine learning (ML) and high-performance computing (HPC) on AWS run compute-intensive workloads across industries and emerging applications. Its use cases can be linked to various verticals, such as computational fluid dynamics (CFD), genomics, and autonomous vehicles. This book provides end-to-end guidance, starting with HPC concepts for storage and networking. It then progresses to working examples on how to process large datasets using SageMaker Studio and EMR. Next, you'll learn how to build, train, and deploy large models using distributed training. Later chapters also guide you through deploying models to edge devices using SageMaker and IoT Greengrass, and performance optimization of ML models, for low latency use cases. By the end of this book, you'll be able to build, train, and deploy your own large-scale ML application, using HPC on AWS, following industry best practices and addressing the key pain points encountered in the application life cycle. What you will learnExplore data management, storage, and fast networking for HPC applicationsFocus on the analysis and visualization of a large volume of data using SparkTrain visual transformer models using SageMaker distributed trainingDeploy and manage ML models at scale on the cloud and at the edgeGet to grips with performance optimization of ML models for low latency workloadsApply HPC to industry domains such as CFD, genomics, AV, and optimizationWho this book is for The book begins with HPC concepts, however, it expects you to have prior machine learning knowledge. This book is for ML engineers and data scientists interested in learning advanced topics on using large datasets for training large models using distributed training concepts on AWS, deploying models at scale, and performance optimization for low latency use cases. Practitioners in fields such as numerical optimization, computation fluid dynamics, autonomous vehicles, and genomics, who require HPC for applying ML models to applications at scale will also find the book useful.
Optimizing Your Modernization Journey With Aws
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Author : Mridula Grandhi
language : en
Publisher: Packt Publishing Ltd
Release Date : 2023-07-07
Optimizing Your Modernization Journey With Aws written by Mridula Grandhi and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-07 with Computers categories.
A strategic guide that will help you make key decisions related to cloud-based architectures, modernize your infrastructure and applications, and transform your business using AWS with real-world case studies Key Features Learn cloud migration and modernization strategies on AWS Innovate your applications, data, architecture and networking by adopting AWS Leverage AWS technologies with real world use-cases to implement cloud operations Purchase of the print or Kindle book includes a free eBook in the PDF format Book Description AWS cloud technologies help businesses scale and innovate, however, adopting modern architecture and applications can be a real challenge. This book is a comprehensive guide that ensures your switch to AWS services is smooth and hitch-free. It will enable you to make optimal decisions to bring out the best ROI from AWS cloud adoption. Beginning with nuances of cloud transformation on AWS, you'll be able to plan and implement the migration steps. The book will facilitate your system modernization journey by getting you acquainted with various technical domains, namely, applications, databases, big data, analytics, networking, and security. Once you've learned about the different operations, budgeting, and management best practices such as the 6 Rs of migration approaches and the AWS Well-Architected Framework, you'll be able to achieve operational excellence in cloud adoption. You'll also learn how to deploy some of the important AWS tools and services with real-life case studies and use cases. By the end of this book, you'll be able to successfully implement cloud migration and modernization on AWS and make decisions that best suit your organization. What you will learn Strategize approaches for cloud adoption and digital transformation Understand the catalysts for business reinvention Select the right tools for cloud migration and modernization processes Leverage the potential of AWS to maximize the value of cloud investments Understand the importance of implementing secure workloads on the cloud Explore AWS services such as computation, databases, security, and networking Implement various real-life use cases and technology case studies for modernization Discover the benefits of operational excellence on the cloud Who this book is for If you are a cloud enthusiast, solutions architect, enterprise technologist, or a C-suite executive and want to learn about the strategies and AWS services to transform your IT portfolio, this book is for you. Basic knowledge of AWS services and an understanding of technologies such as computation, databases, networking, and security will be helpful.
Google Cloud Developer Certification
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Author : Cybellium
language : en
Publisher: Cybellium Ltd
Release Date : 2024-10-26
Google Cloud Developer Certification written by Cybellium and has been published by Cybellium Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-26 with Computers categories.
Designed for professionals, students, and enthusiasts alike, our comprehensive books empower you to stay ahead in a rapidly evolving digital world. * Expert Insights: Our books provide deep, actionable insights that bridge the gap between theory and practical application. * Up-to-Date Content: Stay current with the latest advancements, trends, and best practices in IT, Al, Cybersecurity, Business, Economics and Science. Each guide is regularly updated to reflect the newest developments and challenges. * Comprehensive Coverage: Whether you're a beginner or an advanced learner, Cybellium books cover a wide range of topics, from foundational principles to specialized knowledge, tailored to your level of expertise. Become part of a global network of learners and professionals who trust Cybellium to guide their educational journey. www.cybellium.com
Cloud Architecture For Enterprise Applications Designing Scalable And Secure Cloud Solutions
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Author : ARAVIND AYYAGARI DINESH NAYAK AFROZ SHAIK OM GOEL
language : en
Publisher: DeepMisti Publication
Release Date : 2024-11-09
Cloud Architecture For Enterprise Applications Designing Scalable And Secure Cloud Solutions written by ARAVIND AYYAGARI DINESH NAYAK AFROZ SHAIK OM GOEL and has been published by DeepMisti Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-09 with Computers categories.
In the rapidly evolving landscape of technology, the design and implementation of cloud architectures have become crucial for organizations aiming to build scalable and secure enterprise applications. This book, Cloud Architecture for Enterprise Applications – Designing Scalable and Secure Cloud Solutions, is intended to bridge the gap between innovative cloud solutions and their practical applications in enterprise environments. Our goal is to provide readers with the knowledge and tools necessary to understand and design cloud architectures that meet modern business demands for scalability, security, and performance. This book offers a comprehensive exploration of the methodologies, architectural patterns, and strategies essential for developing cloud solutions, focusing on their integration into enterprise systems. From foundational cloud computing principles to advanced applications in cloud security, performance optimization, and multi-cloud strategies, we delve into the critical components that power successful enterprise applications. Complex technical concepts are presented in a clear and accessible way, making this book suitable for a wide audience, including cloud architects, IT professionals, developers, and business leaders. In crafting this work, we have drawn upon the latest research and industry best practices to ensure readers not only gain a solid theoretical grounding but also acquire practical skills that can be applied in real-world scenarios. Each chapter strikes a balance between depth and breadth, covering topics ranging from cloud migration strategies and serverless computing to data privacy, compliance, and disaster recovery in cloud environments. Moreover, we emphasize the importance of security in cloud architecture, dedicating sections to best practices for safeguarding sensitive enterprise data and ensuring compliance with industry regulations. The inspiration for this book comes from the growing need to equip organizations with the tools and knowledge to navigate the complexities of cloud computing. We are deeply grateful to Chancellor Shri Shiv Kumar Gupta of Maharaja Agrasen Himalayan Garhwal University for his unwavering support and vision. His commitment to promoting academic excellence and fostering technological innovation has been instrumental in the realization of this project. We hope this book will serve as a valuable resource and inspiration for those seeking to deepen their understanding of cloud architecture and its transformative impact on enterprise applications. We believe that the insights and knowledge presented within these pages will empower readers to lead the way in developing innovative cloud solutions that will shape the future of enterprise technology. Thank you for embarking on this journey with us. Authors
Edge Computing
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Author : Weisong Shi
language : en
Publisher: John Wiley & Sons
Release Date : 2025-06-17
Edge Computing written by Weisong Shi and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-17 with Computers categories.
Understand the computing technology that will power a connected future The explosive growth of the Internet of Things (IoT) in recent years has revolutionized virtually every area of technology. It has also driven a drastically increased demand for computing power, as traditional cloud computing proved insufficient in terms of bandwidth, latency, and privacy. Edge computing, in which data is processed at the edge of the network, closer to where it's generated, has emerged as an alternative which meets the new data needs of an increasingly connected world. Edge Computing offers a thorough but accessible overview of this cutting-edge technology. Beginning with the fundamentals of edge computing, including its history, key characteristics, and use cases, it describes the architecture and infrastructure of edge computing and the hardware that enables it. The book also explores edge intelligence, where artificial intelligence is integrated into edge computing to enable smaller, faster, and more autonomous decision-making. The result is an essential tool for any researcher looking to understand this increasingly ubiquitous method for processing data. Edge Computing readers will also find: Real-world applications and case studies drawn from industries including healthcare and urban development Detailed discussion of topics including latency, security, privacy, and scalability A concluding summary of key findings and a look forward at an evolving computing landscape Edge Computing is ideal for students, professionals, and enthusiasts looking to understand one of technology's most exciting new paradigms.
Mobile Edge Computing And Communications
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Author : Aaron Yi Ding
language : en
Publisher: John Wiley & Sons
Release Date : 2024-12-27
Mobile Edge Computing And Communications written by Aaron Yi Ding and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-27 with Technology & Engineering categories.
An up-to-date and comprehensive guide to mobile edge computing and communications Mobile Edge Computing and Communications offers a practical guide to mobile edge computing and communications (MEC). With contributions from noted experts on the topic, the book covers the design, deployment, and operational aspects of this rapidly growing domain. The text provides the information needed to understand the mainstream system architectures and integration methods that have been proposed in MEC. In addition, the book clearly illustrates critical lifecycle functions and stages of MEC, and shows how to deploy MEC in 5G and beyond mobile networks. Comprehensive in scope, the book contains discussions on the challenges and opportunities of mobile edge computing and communications concepts combined with the most relevant emerging applications and services. The authors provide insights for all relative stakeholders of mobile networks such as mobile network operators. This important book: Provides a comprehensive walkthrough of mobile edge computing and communications Includes detailed analysis of current edge applications and technology foundation Presents information on driving forces and future directions of MEC Provides an authentic source of information from industry experts to drive the future of computing Written for mobile network operators, ICT service developers, academic researchers, undergraduate and graduate students, Mobile Edge Computing and Communications offers a guide to the current and future of MEC that will enable a completely new paradigm for future computing and communications.
Snowflake The Definitive Guide
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Author : Joyce Kay Avila
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2022-08-11
Snowflake The Definitive Guide written by Joyce Kay Avila and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-11 with Computers categories.
Snowflake's ability to eliminate data silos and run workloads from a single platform creates opportunities to democratize data analytics, allowing users at all levels within an organization to make data-driven decisions. Whether you're an IT professional working in data warehousing or data science, a business analyst or technical manager, or an aspiring data professional wanting to get more hands-on experience with the Snowflake platform, this book is for you. You'll learn how Snowflake users can build modern integrated data applications and develop new revenue streams based on data. Using hands-on SQL examples, you'll also discover how the Snowflake Data Cloud helps you accelerate data science by avoiding replatforming or migrating data unnecessarily. You'll be able to: Efficiently capture, store, and process large amounts of data at an amazing speed Ingest and transform real-time data feeds in both structured and semistructured formats and deliver meaningful data insights within minutes Use Snowflake Time Travel and zero-copy cloning to produce a sensible data recovery strategy that balances system resilience with ongoing storage costs Securely share data and reduce or eliminate data integration costs by accessing ready-to-query datasets available in the Snowflake Marketplace
Amazon Sagemaker Best Practices
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Author : Sireesha Muppala
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-09-24
Amazon Sagemaker Best Practices written by Sireesha Muppala and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-24 with Computers categories.
Overcome advanced challenges in building end-to-end ML solutions by leveraging the capabilities of Amazon SageMaker for developing and integrating ML models into production Key FeaturesLearn best practices for all phases of building machine learning solutions - from data preparation to monitoring models in productionAutomate end-to-end machine learning workflows with Amazon SageMaker and related AWSDesign, architect, and operate machine learning workloads in the AWS CloudBook Description Amazon SageMaker is a fully managed AWS service that provides the ability to build, train, deploy, and monitor machine learning models. The book begins with a high-level overview of Amazon SageMaker capabilities that map to the various phases of the machine learning process to help set the right foundation. You'll learn efficient tactics to address data science challenges such as processing data at scale, data preparation, connecting to big data pipelines, identifying data bias, running A/B tests, and model explainability using Amazon SageMaker. As you advance, you'll understand how you can tackle the challenge of training at scale, including how to use large data sets while saving costs, monitoring training resources to identify bottlenecks, speeding up long training jobs, and tracking multiple models trained for a common goal. Moving ahead, you'll find out how you can integrate Amazon SageMaker with other AWS to build reliable, cost-optimized, and automated machine learning applications. In addition to this, you'll build ML pipelines integrated with MLOps principles and apply best practices to build secure and performant solutions. By the end of the book, you'll confidently be able to apply Amazon SageMaker's wide range of capabilities to the full spectrum of machine learning workflows. What you will learnPerform data bias detection with AWS Data Wrangler and SageMaker ClarifySpeed up data processing with SageMaker Feature StoreOvercome labeling bias with SageMaker Ground TruthImprove training time with the monitoring and profiling capabilities of SageMaker DebuggerAddress the challenge of model deployment automation with CI/CD using the SageMaker model registryExplore SageMaker Neo for model optimizationImplement data and model quality monitoring with Amazon Model MonitorImprove training time and reduce costs with SageMaker data and model parallelismWho this book is for This book is for expert data scientists responsible for building machine learning applications using Amazon SageMaker. Working knowledge of Amazon SageMaker, machine learning, deep learning, and experience using Jupyter Notebooks and Python is expected. Basic knowledge of AWS related to data, security, and monitoring will help you make the most of the book.
Applied Machine Learning And High Performance Computing On Aws
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Author : Mani Khanuja
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-12-30
Applied Machine Learning And High Performance Computing On Aws written by Mani Khanuja and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-30 with Computers categories.
Build, train, and deploy large machine learning models at scale in various domains such as computational fluid dynamics, genomics, autonomous vehicles, and numerical optimization using Amazon SageMaker Key FeaturesUnderstand the need for high-performance computing (HPC)Build, train, and deploy large ML models with billions of parameters using Amazon SageMakerLearn best practices and architectures for implementing ML at scale using HPCBook Description Machine learning (ML) and high-performance computing (HPC) on AWS run compute-intensive workloads across industries and emerging applications. Its use cases can be linked to various verticals, such as computational fluid dynamics (CFD), genomics, and autonomous vehicles. This book provides end-to-end guidance, starting with HPC concepts for storage and networking. It then progresses to working examples on how to process large datasets using SageMaker Studio and EMR. Next, you'll learn how to build, train, and deploy large models using distributed training. Later chapters also guide you through deploying models to edge devices using SageMaker and IoT Greengrass, and performance optimization of ML models, for low latency use cases. By the end of this book, you'll be able to build, train, and deploy your own large-scale ML application, using HPC on AWS, following industry best practices and addressing the key pain points encountered in the application life cycle. What you will learnExplore data management, storage, and fast networking for HPC applicationsFocus on the analysis and visualization of a large volume of data using SparkTrain visual transformer models using SageMaker distributed trainingDeploy and manage ML models at scale on the cloud and at the edgeGet to grips with performance optimization of ML models for low latency workloadsApply HPC to industry domains such as CFD, genomics, AV, and optimizationWho this book is for The book begins with HPC concepts, however, it expects you to have prior machine learning knowledge. This book is for ML engineers and data scientists interested in learning advanced topics on using large datasets for training large models using distributed training concepts on AWS, deploying models at scale, and performance optimization for low latency use cases. Practitioners in fields such as numerical optimization, computation fluid dynamics, autonomous vehicles, and genomics, who require HPC for applying ML models to applications at scale will also find the book useful.