{"product_id":"getting-started-with-amazon-sagemaker-studio-learn-to-build-end-to-end-machine-learning-projects-in-the-sagemaker-machine-learning-ide-paperback","title":"Getting Started with Amazon SageMaker Studio: Learn to build end-to-end machine learning projects in the SageMaker machine learning IDE - Paperback","description":"\u003cp\u003eby \u003cb\u003eMichael Hsieh\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eBuild 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\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\u003eUnderstand the ML lifecycle in the cloud and its development on Amazon SageMaker Studio\u003c\/li\u003e\n\u003cli\u003eLearn to apply SageMaker features in SageMaker Studio for ML use cases\u003c\/li\u003e\n\u003cli\u003eScale and operationalize the ML lifecycle effectively using SageMaker Studio\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 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.\u003c\/p\u003e\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003eIn 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 how these features work together to address common challenges when building ML models in production. After that, you'll understand how to effectively scale and operationalize the ML life cycle using SageMaker Studio.\u003c\/p\u003e\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003eBy the end of this book, you'll have learned ML best practices regarding Amazon SageMaker Studio, as well as being able to improve productivity in the ML development life cycle and build and deploy models easily for your ML use cases.\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\u003eExplore the ML development life cycle in the cloud\u003c\/li\u003e\n\u003cli\u003eUnderstand SageMaker Studio features and the user interface\u003c\/li\u003e\n\u003cli\u003eBuild a dataset with clicks and host a feature store for ML\u003c\/li\u003e\n\u003cli\u003eTrain ML models with ease and scale\u003c\/li\u003e\n\u003cli\u003eCreate ML models and solutions with little code\u003c\/li\u003e\n\u003cli\u003eHost ML models in the cloud with optimal cloud resources\u003c\/li\u003e\n\u003cli\u003eEnsure optimal model performance with model monitoring\u003c\/li\u003e\n\u003cli\u003eApply governance and operational excellence to ML projects\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 data scientists and machine learning engineers who are looking to become well-versed with Amazon SageMaker Studio and gain hands-on machine learning experience to handle every step in the ML lifecycle, including building data as well as training and hosting models. Although basic knowledge of machine learning and data science is necessary, no previous knowledge of SageMaker Studio and cloud experience is required.\u003c\/p\u003e\u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 326\u003c\/div\u003e\u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 0.68 x 9.25 x 7.5 IN\u003c\/div\u003e\u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e March 31, 2022\u003c\/div\u003e","brand":"Books by splitShops","offers":[{"title":"Default Title","offer_id":47409378164914,"sku":"9781801070157","price":63.34,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0770\/3891\/1666\/files\/025f7c4e712458e5f751c28485b971f0.webp?v=1778264593","url":"https:\/\/box.dadyminds.org\/products\/getting-started-with-amazon-sagemaker-studio-learn-to-build-end-to-end-machine-learning-projects-in-the-sagemaker-machine-learning-ide-paperback","provider":"DADYMINDS BOX","version":"1.0","type":"link"}