chris fregly antje barth (48 resultados)

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Condición: New. Idioma/Language: Español. Las empresas de hoy en día avanzan rápidamente para integrar la inteligencia artificial generativa en sus productos y servicios. Hay mucha agitación (y también malentendidos) sobre el impacto y la promesa de esta tecnología. Con este libro, Chris Fregly, Antje Barth y Shelbee Eigenbrode, de Amazon Web Services, le ayudarán a encontrar formas prácticas de usar esta tecnología tan nueva y atractiva. Gracias a IA generativa en AWS, descubrirá el ciclo de vida de los proyectos de IA generativa, que incluye la definición de casos de uso, la selección y el ajuste de los modelos, la generación mejorada por recuperación, el aprendizaje por refuerzo a partir de la retroalimentación humana y la cuantificación, la optimización y el despliegue de los modelos. Además, explorará diferentes tipos de modelos, incluidos los modelos de lenguaje grandes (LLM) y los multimodales, como Stable Diffusion para generar imágenes y Flamingo/IDEFICS para responder preguntas sobre imágenes. Asimismo, con esta lectura: o Utilizará la IA generativa en los casos de uso de negocio o Determinará qué modelos de IA generativa son los más adecuados para su tarea o Desarrollará ingeniería de indicaciones y aprendizaje en contexto o Afinará los modelos de IA generativa con los conjuntos de datos con adaptación de rango bajo (LoRA) o Alineará los modelos de IA generativa con los valores humanos con el aprendizaje por refuerzo a partir de la retroalimentación humana (RLHF) o Perfeccionará el modelo con la generación mejorada por recuperación (RAG) o Explorará bibliotecas como LangChain y ReAct para desarrollar agentes y acciones o Creará aplicaciones de IA generativa con Amazon Bedrock No importa si es un director técnico, un profesional de aprendizaje automático (AA), un desarrollador de aplicaciones, un analista de negocios, un ingeniero de datos o un científico de datos; si tiene interés en el mundo de la IA, este libro no le dejará indiferente. Chris Fregly es un arquitecto principal de soluciones para la IA generativa en Amazon Web Services y coautor de Data Science on AWS (O'Reilly). Antje Barth es una desarrolladora principal de IA generativa en Amazon Web Services y coautora de Data Science on AWS. Shelbee Eigenbrode es una arquitecta principal de soluciones para la IA generativa en Amazon Web Services. Posee más de 35 patentes en varios dominios tecnológicos. *** Nota: Los envíos a España peninsular, Baleares y Canarias se realizan a través de mensajería urgente. No aceptamos pedidos con destino a Ceuta y Melilla.

Condición: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher.

Condición: new. New!

Condición: New.

Taschenbuch. Condición: Neu. Neuware - Las empresas de hoy en día avanzan rápidamente para integrar la inteligencia artificial generativa en sus productos y servicios. Hay mucha agitación (y también malentendidos) sobre el impacto y la promesa de esta tecnología. Con este libro, Chris Fregly, Antje Barth y Shelbee Eigenbrode, de Amazon Web Services, le ayudarán a encontrar formas prácticas de usar esta tecnología tan nueva y atractiva. Gracias a IA generativa en AWS, descubrirá el ciclo de vida de los proyectos de IA generativa, que incluye la definición de casos de uso, la selección y el ajuste de los modelos, la generación mejorada por recuperación, el aprendizaje por refuerzo a partir de la retroalimentación humana y la cuantificación, la optimización y el despliegue de los modelos. Además, explorará diferentes tipos de modelos, incluidos los modelos de lenguaje grandes (LLM) y los multimodales, como Stable Diffusion para generar imágenes y Flamingo/IDEFICS para responder preguntas sobre imágenes. Asimismo, con esta lectura: o Utilizará la IA generativa en los casos de uso de negocio o Determinará qué modelos de IA generativa son los más adecuados para su tarea o Desarrollará ingeniería de indicaciones y aprendizaje en contexto o Afinará los modelos de IA generativa con los conjuntos de datos con adaptación de rango bajo (LoRA) o Alineará los modelos de IA generativa con los valores humanos con el aprendizaje por refuerzo a partir de la retroalimentación humana (RLHF) o Perfeccionará el modelo con la generación mejorada por recuperación (RAG) o Explorará bibliotecas como LangChain y ReAct para desarrollar agentes y acciones o Creará aplicaciones de IA generativa con Amazon Bedrock No importa si es un director técnico, un profesional de aprendizaje automático (AA), un desarrollador de aplicaciones, un analista de negocios, un ingeniero de datos o un científico de datos; si tiene interés en el mundo de la IA, este libro no le dejará indiferente. Chris Fregly es un arquitecto principal de soluciones para la IA generativa en Amazon Web Services y coautor de Data Science on AWS (O'Reilly). Antje Barth es una desarrolladora principal de IA generativa en Amazon Web Services y coautora de Data Science on AWS. Shelbee Eigenbrode es una arquitecta principal de soluciones para la IA generativa en Amazon Web Services. Posee más de 35 patentes en varios dominios tecnológicos.

paperback. Condición: Very Good. Clean, unmarked pages, minor wear to cover.

Condición: NEW.

Condición: New. In.

Condición: New. In.

Paperback. Condición: New. With this practical book, AI and machine learning practitioners will learn how to successfully build and deploy data science projects on Amazon Web Services. The Amazon AI and machine learning stack unifies data science, data engineering, and application development to help level up your skills. This guide shows you how to build and run pipelines in the cloud, then integrate the results into applications in minutes instead of days. Throughout the book, authors Chris Fregly and Antje Barth demonstrate how to reduce cost and improve performance.Apply the Amazon AI and ML stack to real-world use cases for natural language processing, computer vision, fraud detection, conversational devices, and moreUse automated machine learning to implement a specific subset of use cases with Amazon SageMaker AutopilotDive deep into the complete model development lifecycle for a BERT-based NLP use case including data ingestion, analysis, and moreTie everything together into a repeatable machine learning operations pipelineExplore real-time ML, anomaly detection, and streaming analytics on data streams with Amazon Kinesis and Managed Streaming for Apache KafkaLearn security best practices for data science projects and workflows including identity and access management, authentication, authorization, and more.

Condición: New.

Condición: New.

Paperback. Condición: New. With this practical book, AI and machine learning practitioners will learn how to successfully build and deploy data science projects on Amazon Web Services. The Amazon AI and machine learning stack unifies data science, data engineering, and application development to help level up your skills. This guide shows you how to build and run pipelines in the cloud, then integrate the results into applications in minutes instead of days. Throughout the book, authors Chris Fregly and Antje Barth demonstrate how to reduce cost and improve performance.Apply the Amazon AI and ML stack to real-world use cases for natural language processing, computer vision, fraud detection, conversational devices, and moreUse automated machine learning to implement a specific subset of use cases with Amazon SageMaker AutopilotDive deep into the complete model development lifecycle for a BERT-based NLP use case including data ingestion, analysis, and moreTie everything together into a repeatable machine learning operations pipelineExplore real-time ML, anomaly detection, and streaming analytics on data streams with Amazon Kinesis and Managed Streaming for Apache KafkaLearn security best practices for data science projects and workflows including identity and access management, authentication, authorization, and more.

Condición: New.

Condición: New.

Condición: New.

Condición: New. 2023. 1st Edition. paperback. . . . . .

Paperback. Condición: New. Companies today are moving rapidly to integrate generative AI into their products and services. But there's a great deal of hype (and misunderstanding) about the impact and promise of this technology. With this book, Chris Fregly, Antje Barth, and Shelbee Eigenbrode from AWS help CTOs, ML practitioners, application developers, business analysts, data engineers, and data scientists find practical ways to use this exciting new technology.You'll learn the generative AI project life cycle including use case definition, model selection, model fine-tuning, retrieval-augmented generation, reinforcement learning from human feedback, and model quantization, optimization, and deployment. And you'll explore different types of models including large language models (LLMs) and multimodal models such as Stable Diffusion for generating images and Flamingo/IDEFICS for answering questions about images.Apply generative AI to your business use casesDetermine which generative AI models are best suited to your taskPerform prompt engineering and in-context learningFine-tune generative AI models on your datasets with low-rank adaptation (LoRA)Align generative AI models to human values with reinforcement learning from human feedback (RLHF)Augment your model with retrieval-augmented generation (RAG)Explore libraries such as LangChain and ReAct to develop agents and actionsBuild generative AI applications with Amazon Bedrock.

Paperback. Condición: New. Companies today are moving rapidly to integrate generative AI into their products and services. But there's a great deal of hype (and misunderstanding) about the impact and promise of this technology. With this book, Chris Fregly, Antje Barth, and Shelbee Eigenbrode from AWS help CTOs, ML practitioners, application developers, business analysts, data engineers, and data scientists find practical ways to use this exciting new technology.You'll learn the generative AI project life cycle including use case definition, model selection, model fine-tuning, retrieval-augmented generation, reinforcement learning from human feedback, and model quantization, optimization, and deployment. And you'll explore different types of models including large language models (LLMs) and multimodal models such as Stable Diffusion for generating images and Flamingo/IDEFICS for answering questions about images.Apply generative AI to your business use casesDetermine which generative AI models are best suited to your taskPerform prompt engineering and in-context learningFine-tune generative AI models on your datasets with low-rank adaptation (LoRA)Align generative AI models to human values with reinforcement learning from human feedback (RLHF)Augment your model with retrieval-augmented generation (RAG)Explore libraries such as LangChain and ReAct to develop agents and actionsBuild generative AI applications with Amazon Bedrock.

Condición: As New. Unread book in perfect condition.

Paperback. Condición: New. Companies today are moving rapidly to integrate generative AI into their products and services. But there's a great deal of hype (and misunderstanding) about the impact and promise of this technology. With this book, Chris Fregly, Antje Barth, and Shelbee Eigenbrode from AWS help CTOs, ML practitioners, application developers, business analysts, data engineers, and data scientists find practical ways to use this exciting new technology.You'll learn the generative AI project life cycle including use case definition, model selection, model fine-tuning, retrieval-augmented generation, reinforcement learning from human feedback, and model quantization, optimization, and deployment. And you'll explore different types of models including large language models (LLMs) and multimodal models such as Stable Diffusion for generating images and Flamingo/IDEFICS for answering questions about images.Apply generative AI to your business use casesDetermine which generative AI models are best suited to your taskPerform prompt engineering and in-context learningFine-tune generative AI models on your datasets with low-rank adaptation (LoRA)Align generative AI models to human values with reinforcement learning from human feedback (RLHF)Augment your model with retrieval-augmented generation (RAG)Explore libraries such as LangChain and ReAct to develop agents and actionsBuild generative AI applications with Amazon Bedrock.

Condición: New. This guide shows you how to build and run pipelines in the cloud, then integrate the results into applications in minutes instead of days. Throughout the book, authors Chris Fregly and Antje Barth demonstrate how to reduce cost and improve performance.

Condición: new. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Condición: As New. Unread book in perfect condition.

Condición: As New. Unread book in perfect condition.

Paperback. Condición: New. Companies today are moving rapidly to integrate generative AI into their products and services. But there's a great deal of hype (and misunderstanding) about the impact and promise of this technology. With this book, Chris Fregly, Antje Barth, and Shelbee Eigenbrode from AWS help CTOs, ML practitioners, application developers, business analysts, data engineers, and data scientists find practical ways to use this exciting new technology.You'll learn the generative AI project life cycle including use case definition, model selection, model fine-tuning, retrieval-augmented generation, reinforcement learning from human feedback, and model quantization, optimization, and deployment. And you'll explore different types of models including large language models (LLMs) and multimodal models such as Stable Diffusion for generating images and Flamingo/IDEFICS for answering questions about images.Apply generative AI to your business use casesDetermine which generative AI models are best suited to your taskPerform prompt engineering and in-context learningFine-tune generative AI models on your datasets with low-rank adaptation (LoRA)Align generative AI models to human values with reinforcement learning from human feedback (RLHF)Augment your model with retrieval-augmented generation (RAG)Explore libraries such as LangChain and ReAct to develop agents and actionsBuild generative AI applications with Amazon Bedrock.