sagemaker

Continuous Machine Learning with Kubeflow Performing Reliable MLOps with Capabilities of TFX, Sagemaker and Kubernetes (English Edition)【電子書籍】 Aniruddha ChoudhuryCloud Native AI and Machine Learning on AWS Use SageMaker for building ML models, automate MLOps, and take advantage of numerous AWS AI services (English Edition)【電子書籍】 Premkumar Rangarajanソーセージメーカー 手動ソーセージメーカー ソーセージマシン 腸詰め器 ソーセージスタッファー ソーセージ充填器 sausage makerアルミ合金製 錆止め 自家製ソーセージ ホームキッチン ホッ洋書 Manning Publications Paperback, Machine Learning for Business: Using Amazon SageMaker and JupyterAmazon SageMaker Best Practices Proven tips and tricks to build successful machine learning solutions on Amazon SageMaker【電子書籍】 Sireesha MuppalaBeginning MLOps with MLFlow Deploy Models in AWS SageMaker, Google Cloud, and Microsoft Azure【電子書籍】 Sridhar AllaLearn Amazon SageMaker A guide to building, training, and deploying machine learning models for developers and data scientists【電子書籍】 Julien SimonCloud Native AI and Machine Learning on AWS: Use SageMaker for building ML models, automate MLOps, and take advantage of numerous AWS AI services (English Edition)【電子書籍】 Premkumar Rangarajanソーセージメーカー 手動ソーセージメーカー ソーセージマシン 腸詰め器 ソーセージスタッファー ソーセージ充填器 sausage makerアルミ合金製 錆止め 自家製ソーセージ ホームキッチン ホッContinuous Machine Learning with Kubeflow: Performing Reliable MLOps with Capabilities of TFX, Sagemaker and Kubernetes (English Edition)【電子書籍】 Aniruddha ChoudhuryComputer Vision on AWS Build and deploy real-world CV solutions with Amazon Rekognition, Lookout for Vision, and SageMaker【電子書籍】 Lauren MullennexLearn Amazon SageMaker A guide to building, training, and deploying machine learning models for developers and data scientists【電子書籍】 Julien SimonMastering Machine Learning on AWS Advanced machine learning in Python using SageMaker, Apache Spark, and TensorFlow【電子書籍】 Dr. Saket S.R. MengleMachine Learning in the AWS Cloud Add Intelligence to Applications with Amazon SageMaker and Amazon Rekognition【電子書籍】 Abhishek Mishra洋書 Wiley-Interscience Paperback, Machine Learning in the AWS Cloud: Add Intelligence to Applications with Amazon SageMaker and Amazon RekognitionAccelerate Deep Learning Workloads with Amazon SageMaker Train, deploy, and scale deep learning models effectively using Amazon SageMaker【電子書籍】 Vadim Dabravolski洋書 Paperback, Mastering Machine Learning on AWS: Advanced machine learning in Python using SageMaker, Apache Spark, and TensorFlowMachine Learning with Amazon SageMaker Cookbook 80 proven recipes for data scientists and developers to perform machine learning experiments and deployments【電子書籍】 Joshua Arvin LatGetting Started with Amazon SageMaker Studio Learn to build end-to-end machine learning projects in the SageMaker machine learning IDE【電子書籍】 Michael Hsiehソーセージメーカー 手動ソーセージメーカー ソーセージマシン 腸詰め器 ソーセージスタッファー ソーセージ充填器 sausage makerアルミ合金製 錆止め 自家製ソーセージ ホームキッチン ホットドッグ ホットリンク 家庭用 業務用 2ポン SISB

Continuous Machine Learning with Kubeflow Performing Reliable MLOps with Capabilities of TFX, Sagemaker and Kubernetes (English Edition)【電子書籍】[ Aniruddha Choudhury ]

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  • ＜p＞Continuous Machine Learning with Kubeflow' introduces you to the modern machine learning infrastructure, which includes Kubernetes and the Kubeflow architecture. This book will explain the fundamentals of deploying various AI/ML use cases with TensorFlow training and serving with Kubernetes and how Kubernetes can help with specific projects from start to finish.This book will help demonstrate how to use Kubeflow components, deploy them in GCP, and serve them in production using real-time data prediction. With Kubeflow KFserving, we'll look at serving techniques, build a computer vision-based user interface in streamlit, and then deploy it to the Google cloud platforms, Kubernetes and Heroku. Next, we also explore how to build Explainable AI for determining fairness and biasness with a What-if tool. Backed with various use-cases, we will learn how to put machine learning into production, including training and serving. After reading this book, you will be able to build your ML p...

    • Cloud Native AI and Machine Learning on AWS Use SageMaker for building ML models, automate MLOps, and take advantage of numerous AWS AI services (English Edition)【電子書籍】[ Premkumar Rangarajan ]

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  • ＜p＞Using machine learning and artificial intelligence (AI) in existing business processes has been successful. Even AWS's ML and AI services make it simple and economical to conduct machine learning experiments. This book will show readers how to use the complete set of AI and ML services available on AWS to streamline the management of their whole AI operation and speed up their innovation.In this book, you'll learn how to build data lakes, build and train machine learning models, automate MLOps, ensure maximum data reusability and reproducibility, and much more. The applications presented in the book show how to make the most of several different AWS offerings, including Amazon Comprehend, Amazon Rekognition, Amazon Lookout, and AutoML. This book teaches you to manage massive data lakes, train artificial intelligence models, release these applications into production, and track their progress in real-time. You will learn how to use the pre-trained models for various tasks, inclu...

    • ソーセージメーカー 手動ソーセージメーカー ソーセージマシン 腸詰め器 ソーセージスタッファー ソーセージ充填器 sausage makerアルミ合金製 錆止め 自家製ソーセージ ホームキッチン ホッ

    ショップ ドリームストア365
    価格 ￥5,728 
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  • ソーセージメーカー 手動ソーセージメーカー ソーセージマシン 腸詰め器 ソーセージスタッファー ソーセージ充填器 sausage makerアルミ合金製 錆止め 自家製ソーセージ ホームキッチン ホットドッグ ホットリンク 家庭用 業務用 2ポン SISBRLR勧め理由理由：この手動ソーセージメーカーがあり、自宅で簡単に新鮮なソーセージを作ることができますアルミ合金製：食品グレードのアルミ合金素材でできており、安全で、錆止め、衛生的で耐久性がありますソーセージ充填器：さまざまなニーズに合わせて、3つの異なるサイズの充填ノズルが付属しています簡単な操作：吸盤固定ベースのソーセージスタッファーは、頑丈で簡単な操作のために好まれます適用：肉、スクイズ麺、ソーセージ、ホットドッグ、ソーセージ、ホットリンク、手作りハンバーグ、 鶏肉、魚、海老、ホットリンク野菜などに幅広くお使いいただけます。<br>商標登録済：登録第6593732号（SISIBRLR）

    • 洋書 Manning Publications Paperback, Machine Learning for Business: Using Amazon SageMaker and Jupyter

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  • *** We ship internationally, so do not use a package forwarding service. We cannot ship to a package forwarding company address because of the Japanese customs regulation. If it is shipped and customs office does not let the package go, we do not make a refund. 【注意事項】 *** 特に注意してください。 *** ・個人ではない法人・団体名義での購入はできません。この場合税関で滅却されてもお客様負担になりますので御了承願います。 ・お名前にカタカナが入っている場合法人である可能性が高いため当店システムから自動保留します。カタカナで記載が必要な場合はカタカナ変わりローマ字で記載してください。 ・お名前またはご住所が法人・団体名義（XX株式会社等）、商店名などを含めている場合、または電話番号が個人のものではない場合、税関から法人名義でみなされますのでご注意ください。 ・転送サービス会社への発送もできません。この場合税関で滅却されてもお客様負担になりますので御了承願います。 *** ・注文後品切れや価格変動でキャンセルされる場合がございますので予めご了承願います。 ・当店でご購入された商品は、原則として、「個...

    • Amazon SageMaker Best Practices Proven tips and tricks to build successful machine learning solutions on Amazon SageMaker【電子書籍】[ Sireesha Muppala ]

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  • ＜p＞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 Features ? Learn best practices for all phases of building machine learning solutions - from data preparation to monitoring models in production ? Automate end-to-end machine learning workflows with Amazon SageMaker and related AWS ? Design, architect, and operate machine learning workloads in the AWS Cloud Book 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, runni...

    • Beginning MLOps with MLFlow Deploy Models in AWS SageMaker, Google Cloud, and Microsoft Azure【電子書籍】[ Sridhar Alla ]

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  • ＜p＞Integrate MLOps principles into existing or future projects using MLFlow, operationalize your models, and deploy them in AWS SageMaker, Google Cloud, and Microsoft Azure. This book guides you through the process of data analysis, model construction, and training.＜/p＞ ＜p＞The authors begin by introducing you to basic data analysis on a credit card data set and teach you how to analyze the features and their relationships to the target variable. You will learn how to build logistic regression models in scikit-learn and PySpark, and you will go through the process of hyperparameter tuning with a validation data set. You will explore three different deployment setups of machine learning models with varying levels of automation to help you better understand MLOps. MLFlow is covered and you will explore how to integrate MLOps into your existing code, allowing you to easily track metrics, parameters, graphs, and models. You will be guided through the process of deploying and queryi...

    • Learn Amazon SageMaker A guide to building, training, and deploying machine learning models for developers and data scientists【電子書籍】[ Julien Simon ]

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  • ＜p＞Swiftly build and deploy machine learning models without managing infrastructure and boost productivity using the latest Amazon SageMaker capabilities such as Studio, Autopilot, Data Wrangler, Pipelines, and Feature Store Key Features ? Build, train, and deploy machine learning models quickly using Amazon SageMaker ? Optimize the accuracy, cost, and fairness of your models ? Create and automate end-to-end machine learning workflows on Amazon Web Services (AWS) Book Description Amazon SageMaker enables you to quickly build, train, and deploy machine learning models at scale without managing any infrastructure. It helps you focus on the machine learning problem at hand and deploy high-quality models by eliminating the heavy lifting typically involved in each step of the ML process. This second edition will help data scientists and ML developers to explore new features such as SageMaker Data Wrangler, Pipelines, Clarify, Feature Store, and much more. You'll start by learning how t...

    • Cloud Native AI and Machine Learning on AWS: Use SageMaker for building ML models, automate MLOps, and take advantage of numerous AWS AI services (English Edition)【電子書籍】[ Premkumar Rangarajan ]

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  • ＜p＞＜strong＞Bring elasticity and innovation to Machine Learning and AI operations＜/strong＞＜/p＞ ＜p＞＜strong＞KEY FEATURES＜/strong＞＜/p＞ ＜p＞● Coverage includes a wide range of AWS AI and ML services to help you speedily get fully operational with ML.＜/p＞ ＜p＞● Packed with real-world examples, practical guides, and expert data science methods for improving AI/ML education on AWS.＜/p＞ ＜p＞● Includes ready-made, purpose-built models as AI services and proven methods to adopt MLOps techniques.＜/p＞ ＜p＞＜strong＞DESCRIPTION＜/strong＞＜/p＞ ＜p＞Using machine learning and artificial intelligence (AI) in existing business processes has been successful. Even AWS's ML and AI services make it simple and economical to conduct machine learning experiments. This book will show readers how to use the complete set of AI and ML services available on AWS to streamline the management of their whole AI operation and speed up their innovation.＜/p＞ ＜p＞In this book, you'll learn...

    • ソーセージメーカー 手動ソーセージメーカー ソーセージマシン 腸詰め器 ソーセージスタッファー ソーセージ充填器 sausage makerアルミ合金製 錆止め 自家製ソーセージ ホームキッチン ホッ

    ショップ ミヤケマーケット
    価格 ￥4,968 
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  • ソーセージメーカー 手動ソーセージメーカー ソーセージマシン 腸詰め器 ソーセージスタッファー ソーセージ充填器 sausage makerアルミ合金製 錆止め 自家製ソーセージ ホームキッチン ホットドッグ ホットリンク 家庭用 業務用 2ポン SISBRLR勧め理由理由：この手動ソーセージメーカーがあり、自宅で簡単に新鮮なソーセージを作ることができますアルミ合金製：食品グレードのアルミ合金素材でできており、安全で、錆止め、衛生的で耐久性がありますソーセージ充填器：さまざまなニーズに合わせて、3つの異なるサイズの充填ノズルが付属しています簡単な操作：吸盤固定ベースのソーセージスタッファーは、頑丈で簡単な操作のために好まれます適用：肉、スクイズ麺、ソーセージ、ホットドッグ、ソーセージ、ホットリンク、手作りハンバーグ、 鶏肉、魚、海老、ホットリンク野菜などに幅広くお使いいただけます。<br>商標登録済：登録第6593732号（SISIBRLR）

    • Continuous Machine Learning with Kubeflow: Performing Reliable MLOps with Capabilities of TFX, Sagemaker and Kubernetes (English Edition)【電子書籍】[ Aniruddha Choudhury ]

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  • ＜p＞An insightful journey to MLOps, DevOps, and Machine Learning in the real environment.＜/p＞ ＜p＞KEY FEATURES＜/p＞ ＜p＞● Extensive knowledge and concept explanation of Kubernetes components with examples.＜/p＞ ＜p＞● An all-in-one knowledge guide to train and deploy ML pipelines using Docker and Kubernetes.＜/p＞ ＜p＞● Includes numerous MLOps projects with access to proven frameworks and the use of deep learning concepts.＜/p＞ ＜p＞DESCRIPTION＜/p＞ ＜p＞'Continuous Machine Learning with Kubeflow' introduces you to the modern machine learning infrastructure, which includes Kubernetes and the Kubeflow architecture. This book will explain the fundamentals of deploying various AI/ML use cases with TensorFlow training and serving with Kubernetes and how Kubernetes can help with specific projects from start to finish.＜/p＞ ＜p＞This book will help demonstrate how to use Kubeflow components, deploy them in GCP, and serve them in production using real-time data prediction. With ...

    • Computer Vision on AWS Build and deploy real-world CV solutions with Amazon Rekognition, Lookout for Vision, and SageMaker【電子書籍】[ Lauren Mullennex ]

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    価格 ￥4,085 
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  • ＜p＞＜strong＞Develop scalable computer vision solutions for real-world business problems and discover scaling, cost reduction, security, and bias mitigation best practices with AWS AI/ML services＜/strong＞＜/p＞ ＜p＞＜strong＞Purchase of the print or Kindle book includes a free PDF eBook＜/strong＞＜/p＞ ＜h4＞Key Features＜/h4＞ ＜ul＞ ＜li＞Learn how to quickly deploy and automate end-to-end CV pipelines on AWS＜/li＞ ＜li＞Implement design principles to mitigate bias and scale production of CV workloads＜/li＞ ＜li＞Work with code examples to master CV concepts using AWS AI/ML services＜/li＞ ＜/ul＞ ＜h4＞Book Description＜/h4＞ ＜p＞Computer vision (CV) is a field of artificial intelligence that helps transform visual data into actionable insights to solve a wide range of business challenges. This book provides prescriptive guidance to anyone looking to learn how to approach CV problems for quickly building and deploying production-ready models.＜/p＞ ＜p＞You'll begin by e...

    • Learn Amazon SageMaker A guide to building, training, and deploying machine learning models for developers and data scientists【電子書籍】[ Julien Simon ]

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    価格 ￥3,858 
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  • ＜p＞＜strong＞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＜/strong＞＜/p＞ ＜h4＞Key Features＜/h4＞ ＜ul＞ ＜li＞Build, train, and deploy machine learning models quickly using Amazon SageMaker＜/li＞ ＜li＞Analyze, detect, and receive alerts relating to various business problems using machine learning algorithms and techniques＜/li＞ ＜li＞Improve productivity by training and fine-tuning machine learning models in production＜/li＞ ＜/ul＞ ＜h4＞Book Description＜/h4＞ ＜p＞Amazon SageMaker enables you to quickly build, train, and deploy machine learning (ML) models at scale, without managing any infrastructure. It helps you focus on the ML problem at hand and deploy high-quality models by removing the heavy lifting typically involved in each step of the ML process. This book is a comprehensive gui...

    • Mastering Machine Learning on AWS Advanced machine learning in Python using SageMaker, Apache Spark, and TensorFlow【電子書籍】[ Dr. Saket S.R. Mengle ]

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    価格 ￥2,950 
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  • ＜p＞＜strong＞Gain expertise in ML techniques with AWS to create interactive apps using SageMaker, Apache Spark, and TensorFlow.＜/strong＞＜/p＞ ＜h4＞Key Features＜/h4＞ ＜ul＞ ＜li＞Build machine learning apps on Amazon Web Services (AWS) using SageMaker, Apache Spark and TensorFlow＜/li＞ ＜li＞Learn model optimization, and understand how to scale your models using simple and secure APIs＜/li＞ ＜li＞Develop, train, tune and deploy neural network models to accelerate model performance in the cloud＜/li＞ ＜/ul＞ ＜h4＞Book Description＜/h4＞ ＜p＞AWS is constantly driving new innovations that empower data scientists to explore a variety of machine learning (ML) cloud services. This book is your comprehensive reference for learning and implementing advanced ML algorithms in AWS cloud.＜/p＞ ＜p＞As you go through the chapters, you'll gain insights into how these algorithms can be trained, tuned and deployed in AWS using Apache Spark on Elastic Map Reduce (EMR), SageMaker, and Te...

    • Machine Learning in the AWS Cloud Add Intelligence to Applications with Amazon SageMaker and Amazon Rekognition【電子書籍】[ Abhishek Mishra ]

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    価格 ￥4,226 
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  • ＜p＞＜strong＞Put the power of AWS Cloud machine learning services to work in your business and commercial applications!＜/strong＞＜/p＞ ＜p＞＜em＞Machine Learning in the AWS Cloud＜/em＞ 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.＜/p＞ ＜p＞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 ...

    • 洋書 Wiley-Interscience Paperback, Machine Learning in the AWS Cloud: Add Intelligence to Applications with Amazon SageMaker and Amazon Rekognition

    ショップ Glomarket
    価格 ￥8,588 
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  • *** We ship internationally, so do not use a package forwarding service. We cannot ship to a package forwarding company address because of the Japanese customs regulation. If it is shipped and customs office does not let the package go, we do not make a refund. 【注意事項】 *** 特に注意してください。 *** ・個人ではない法人・団体名義での購入はできません。この場合税関で滅却されてもお客様負担になりますので御了承願います。 ・お名前にカタカナが入っている場合法人である可能性が高いため当店システムから自動保留します。カタカナで記載が必要な場合はカタカナ変わりローマ字で記載してください。 ・お名前またはご住所が法人・団体名義（XX株式会社等）、商店名などを含めている場合、または電話番号が個人のものではない場合、税関から法人名義でみなされますのでご注意ください。 ・転送サービス会社への発送もできません。この場合税関で滅却されてもお客様負担になりますので御了承願います。 *** ・注文後品切れや価格変動でキャンセルされる場合がございますので予めご了承願います。 ・当店でご購入された商品は、原則として、「個...

    • Accelerate Deep Learning Workloads with Amazon SageMaker Train, deploy, and scale deep learning models effectively using Amazon SageMaker【電子書籍】[ Vadim Dabravolski ]

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    価格 ￥4,312 
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  • ＜p＞Plan and design model serving infrastructure to run and troubleshoot distributed deep learning training jobs for improved model performance. Key Features ? Explore key Amazon SageMaker capabilities in the context of deep learning ? Train and deploy deep learning models using SageMaker managed capabilities and optimize your deep learning workloads ? Cover in detail the theoretical and practical aspects of training and hosting your deep learning models on Amazon SageMaker Book 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 imp...

    • 洋書 Paperback, Mastering Machine Learning on AWS: Advanced machine learning in Python using SageMaker, Apache Spark, and TensorFlow

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    価格 ￥8,724 
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  • *** We ship internationally, so do not use a package forwarding service. We cannot ship to a package forwarding company address because of the Japanese customs regulation. If it is shipped and customs office does not let the package go, we do not make a refund. 【注意事項】 *** 特に注意してください。 *** ・個人ではない法人・団体名義での購入はできません。この場合税関で滅却されてもお客様負担になりますので御了承願います。 ・お名前にカタカナが入っている場合法人である可能性が高いため当店システムから自動保留します。カタカナで記載が必要な場合はカタカナ変わりローマ字で記載してください。 ・お名前またはご住所が法人・団体名義（XX株式会社等）、商店名などを含めている場合、または電話番号が個人のものではない場合、税関から法人名義でみなされますのでご注意ください。 ・転送サービス会社への発送もできません。この場合税関で滅却されてもお客様負担になりますので御了承願います。 *** ・注文後品切れや価格変動でキャンセルされる場合がございますので予めご了承願います。 ・当店でご購入された商品は、原則として、「個...

    • Machine Learning with Amazon SageMaker Cookbook 80 proven recipes for data scientists and developers to perform machine learning experiments and deployments【電子書籍】[ Joshua Arvin Lat ]

    ショップ 楽天Kobo電子書籍ストア
    価格 ￥4,993 
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  • ＜p＞A step-by-step solution-based guide to preparing building, training, and deploying high-quality machine learning models with Amazon SageMaker Key Features ? Perform ML experiments with built-in and custom algorithms in SageMaker ? Explore proven solutions when working with TensorFlow, PyTorch, Hugging Face Transformers, and scikit-learn ? Use the different features and capabilities of SageMaker to automate relevant ML processes Book Description Amazon SageMaker is a fully managed machine learning (ML) service that helps data scientists and ML practitioners manage ML experiments. In this book, you'll use the different capabilities and features of Amazon SageMaker to solve relevant data science and ML problems. This step-by-step guide features 80 proven recipes designed to give you the hands-on machine learning experience needed to contribute to real-world experiments and projects. You'll cover the algorithms and techniques that are commonly used when training and deploying NLP, ...

    • Getting Started with Amazon SageMaker Studio Learn to build end-to-end machine learning projects in the SageMaker machine learning IDE【電子書籍】[ Michael Hsieh ]

    ショップ 楽天Kobo電子書籍ストア
    価格 ￥4,085 
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  • ＜p＞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 Features ? Understand the ML lifecycle in the cloud and its development on Amazon SageMaker Studio ? Learn to apply SageMaker features in SageMaker Studio for ML use cases ? Scale and operationalize the ML lifecycle effectively using SageMaker Studio Book Description Amazon SageMaker Studio is the first integrated development environment (IDE) for machine learning (ML) and is designed to integrate ML workflows: data preparation, feature engineering, statistical bias detection, automated machine learning (AutoML), training, hosting, ML explainability, monitoring, and MLOps in one environment. In this book, you'll start by exploring the features available in Amazon SageMaker Studio to analyze data, develop ML models, and productionize models to meet your goals. As you progress, you will learn...

    • ソーセージメーカー 手動ソーセージメーカー ソーセージマシン 腸詰め器 ソーセージスタッファー ソーセージ充填器 sausage makerアルミ合金製 錆止め 自家製ソーセージ ホームキッチン ホットドッグ ホットリンク 家庭用 業務用 2ポン SISB

    ショップ 湖南オンライン
    価格 ￥5,189 
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  • ・勧め理由理由：この手動ソーセージメーカーがあり、自宅で簡単に新鮮なソーセージを作ることができます・アルミ合金製：食品グレードのアルミ合金素材でできており、安全で、錆止め、衛生的で耐久性があります・ソーセージ充填器：さまざまなニーズに合わせて、3つの異なるサイズの充填ノズルが付属しています・簡単な操作：吸盤固定ベースのソーセージスタッファーは、頑丈で簡単な操作のために好まれます・適用：肉、スクイズ麺、ソーセージ、ホットドッグ、ソーセージ、ホットリンク、手作りハンバーグ、 鶏肉、魚、海老、ホットリンク野菜などに幅広くお使いいただけます。商標登録済：登録第6593732号（SISIBRLR）
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