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Podcasts
Sireesha Muppala, Randy DeFauw, Shelbee Eigenbrode
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.
Chris Fregly, Antje Barth, Shelbee Eigenbrode
Podczas projektowania aplikacji opartych na generatywnej AI trzeba dokonywać wielu wyborów decydujących o jakości danych dostarczanych przez aplikację, jej opłacalności, skalowalności i niezawodności. Decyzje te są tym trudniejsze, że świat generatywnej AI zmienia się niezwykle szybko, a mity i błędne przeświadczenia dotyczące tej technologii mają się świetnie. W tej niezwykle pragmatycznej książce, przeznaczonej dla dyrektorów technicznych, praktyków uczenia maszynowego, twórców aplikacji, analityków biznesowych, inżynierów i badaczy danych, znajdziesz skuteczne techniki używania sztucznej inteligencji. Zaznajomisz się z cyklem życia projektu opartego na generatywnej AI i jej zastosowaniami, a także metodami doboru i dostrajania modeli, generowania danych wspomaganego wyszukiwaniem, uczenia przez wzmacnianie na podstawie informacji zwrotnych od człowieka, kwantyzacji, optymalizacji i wdrażania modeli. Poznasz szczegóły różnych typów modeli, między innymi dużych językowych (LLM), multimodalnych generujących obrazy (Stable Diffusion) i odpowiadających na pytania wizualne (Flamingo/IDEFICS). Dowiedz się, jak: używać generatywnej AI w biznesie dobierać modele generatywnej AI stosować inżynierię monitu i uczenie kontekstowe dostrajać modele przy użyciu własnych zbiorów danych i techniki LoRA korzystać z agentów i akcji za pomocą bibliotek LangChain i ReAct tworzyć aplikacje na bazie usługi Amazon Bedrock To fascynująca książka, rewelacyjna kompozycja niezwykle ważnych informacji, a także szczegółowych, praktycznych kodów, skryptów i instrukcji! Jeff Barr, wiceprezes i główny popularyzator AWS