Accelerate Deep Learning Workloads with Amazon SageMaker Book [PDF] Download

Download the fantastic book titled Accelerate Deep Learning Workloads with Amazon SageMaker written by Vadim Dabravolski, available in its entirety in both PDF and EPUB formats for online reading. This page includes a concise summary, a preview of the book cover, and detailed information about "Accelerate Deep Learning Workloads with Amazon SageMaker", which was released on 28 October 2022. We suggest perusing the summary before initiating your download. This book is a top selection for enthusiasts of the Computers genre.

Summary of Accelerate Deep Learning Workloads with Amazon SageMaker by Vadim Dabravolski PDF

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.


Detail About Accelerate Deep Learning Workloads with Amazon SageMaker PDF

  • Author : Vadim Dabravolski
  • Publisher : Packt Publishing Ltd
  • Genre : Computers
  • Total Pages : 278 pages
  • ISBN : 1801813116
  • PDF File Size : 44,6 Mb
  • Language : English
  • Rating : 4/5 from 21 reviews

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Accelerate Deep Learning Workloads with Amazon SageMaker

Accelerate Deep Learning Workloads with Amazon SageMaker
  • Publisher : Packt Publishing Ltd
  • File Size : 39,9 Mb
  • Release Date : 28 October 2022
GET BOOK

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

Accelerate Deep Learning Workloads with Amazon SageMaker

Accelerate Deep Learning Workloads with Amazon SageMaker
  • Publisher : Packt Publishing Ltd
  • File Size : 54,6 Mb
  • Release Date : 28 October 2022
GET BOOK

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

Amazon SageMaker Best Practices

Amazon SageMaker Best Practices
  • Publisher : Packt Publishing Ltd
  • File Size : 23,5 Mb
  • Release Date : 24 September 2021
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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

Applied Machine Learning and High-Performance Computing on AWS

Applied Machine Learning and High-Performance Computing on AWS
  • Publisher : Packt Publishing Ltd
  • File Size : 39,9 Mb
  • Release Date : 30 December 2022
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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

Applied Machine Learning and High-Performance Computing on AWS

Applied Machine Learning and High-Performance Computing on AWS
  • Publisher : Packt Publishing Ltd
  • File Size : 24,8 Mb
  • Release Date : 30 December 2022
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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

Learn Amazon SageMaker

Learn Amazon SageMaker
  • Publisher : Packt Publishing Ltd
  • File Size : 28,8 Mb
  • Release Date : 27 August 2020
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Quickly build and deploy machine learning models without managing infrastructure, and improve productivity using Amazon SageMaker’s capabilities such as Amazon SageMaker Studio, Autopilot, Experiments, Debugger, and Model Monitor Key

Machine Learning Engineering on AWS

Machine Learning Engineering on AWS
  • Publisher : Packt Publishing Ltd
  • File Size : 27,9 Mb
  • Release Date : 27 October 2022
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Work seamlessly with production-ready machine learning systems and pipelines on AWS by addressing key pain points encountered in the ML life cycle Key FeaturesGain practical knowledge of managing ML workloads

Getting Started with Amazon SageMaker Studio

Getting Started with Amazon SageMaker Studio
  • Publisher : Packt Publishing Ltd
  • File Size : 30,7 Mb
  • Release Date : 31 March 2022
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Build production-grade machine learning models with Amazon SageMaker Studio, the first integrated development environment in the cloud, using real-life machine learning examples and code Key FeaturesUnderstand the ML lifecycle in

Cloud Native AI and Machine Learning on AWS

Cloud Native AI and Machine Learning on AWS
  • Publisher : BPB Publications
  • File Size : 24,9 Mb
  • Release Date : 14 February 2023
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Bring elasticity and innovation to Machine Learning and AI operations KEY FEATURES ● Coverage includes a wide range of AWS AI and ML services to help you speedily get fully operational

Cloud Native AI and Machine Learning on AWS

Cloud Native AI and Machine Learning on AWS
  • Publisher : BPB Publications
  • File Size : 39,9 Mb
  • Release Date : 14 February 2023
GET BOOK

Bring elasticity and innovation to Machine Learning and AI operations KEY FEATURES ● Coverage includes a wide range of AWS AI and ML services to help you speedily get fully operational