{"product_id":"machine-learning-with-amazon-sagemaker-cookbook-80-proven-recipes-for-data-scientists-and-developers-to-perform-machine-learning-experiments-and-depl-paperback","title":"Machine Learning with Amazon SageMaker Cookbook: 80 proven recipes for data scientists and developers to perform machine learning experiments and depl - Paperback","description":"\u003cdiv\u003e\u003cp style=\"text-align: right;\"\u003e\u003ca href=\"https:\/\/reportcopyrightinfringement.com\/\" target=\"_blank\" rel=\"nofollow\"\u003e\u003cb\u003eReport copyright infringement\u003c\/b\u003e\u003c\/a\u003e\u003c\/p\u003e\u003c\/div\u003e\u003cp\u003eby \u003cb\u003eJoshua Arvin Lat\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eA step-by-step solution-based guide to preparing building, training, and deploying high-quality machine learning models with Amazon SageMaker\u003c\/strong\u003e\u003c\/p\u003e\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eKey Features: \u003c\/strong\u003e\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003ePerform ML experiments with built-in and custom algorithms in SageMaker\u003c\/li\u003e\n\u003cli\u003eExplore proven solutions when working with TensorFlow, PyTorch, Hugging Face Transformers, and scikit-learn\u003c\/li\u003e\n\u003cli\u003eUse the different features and capabilities of SageMaker to automate relevant ML processes\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eBook Description: \u003c\/strong\u003e\u003c\/p\u003e\u003cp\u003eAmazon 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.\u003c\/p\u003e\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003eThis 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, time series forecasting, and computer vision models to solve ML problems. You'll explore various solutions for working with deep learning libraries and frameworks such as TensorFlow, PyTorch, and Hugging Face Transformers in Amazon SageMaker. You'll also learn how to use SageMaker Clarify, SageMaker Model Monitor, SageMaker Debugger, and SageMaker Experiments to debug, manage, and monitor multiple ML experiments and deployments. Moreover, you'll have a better understanding of how SageMaker Feature Store, Autopilot, and Pipelines can meet the specific needs of data science teams.\u003c\/p\u003e\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003eBy the end of this book, you'll be able to combine the different solutions you've learned as building blocks to solve real-world ML problems.\u003c\/p\u003e\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eWhat You Will Learn: \u003c\/strong\u003e\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eTrain and deploy NLP, time series forecasting, and computer vision models to solve different business problems\u003c\/li\u003e\n\u003cli\u003ePush the limits of customization in SageMaker using custom container images\u003c\/li\u003e\n\u003cli\u003eUse AutoML capabilities with SageMaker Autopilot to create high-quality models\u003c\/li\u003e\n\u003cli\u003eWork with effective data analysis and preparation techniques\u003c\/li\u003e\n\u003cli\u003eExplore solutions for debugging and managing ML experiments and deployments\u003c\/li\u003e\n\u003cli\u003eDeal with bias detection and ML explainability requirements using SageMaker Clarify\u003c\/li\u003e\n\u003cli\u003eAutomate intermediate and complex deployments and workflows using a variety of solutions\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eWho this book is for: \u003c\/strong\u003e\u003c\/p\u003e\u003cp\u003eThis book is for developers, data scientists, and machine learning practitioners interested in using Amazon SageMaker to build, analyze, and deploy machine learning models with 80 step-by-step recipes. All you need is an AWS account to get things running. Prior knowledge of AWS, machine learning, and the Python programming language will help you to grasp the concepts covered in this book more effectively. \u003c\/p\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 762\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 1.52 x 9.25 x 7.5 IN\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e October 22, 2021\u003c\/div\u003e\n            ","brand":"BooksCloud","offers":[{"title":"Default Title","offer_id":47438617903325,"sku":"9781800567030","price":100.2,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0811\/9867\/8237\/files\/ZTlRUHZtcVpCN0hGRDlwaVdJcHNOQT09.webp?v=1771425058","url":"https:\/\/handfulofbooks.com\/products\/machine-learning-with-amazon-sagemaker-cookbook-80-proven-recipes-for-data-scientists-and-developers-to-perform-machine-learning-experiments-and-depl-paperback","provider":"Handful of Books","version":"1.0","type":"link"}