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Llmops
Llmops
Knygos.lt klubas Knygos.lt nariams
80,70 €
-30%
Įprastai
115,29 €
  • Išsiųsime per 12–18 d.d.
Learning LLMOps can help optimize the development process, ensure reproducibility, scale infrastructure, and enhance security and privacy, resulting in more efficient and effective deployment of large language models. Large language models require a significant amount of computational resources to develop, train, and fine-tune and can quickly become computationally expensive as the model size and training data increases. LLMOps is an infrastructure management framework that helps scale the infr…
  • Leidėjas:
  • ISBN-10: 1098154207
  • ISBN-13: 9781098154202
  • Formatas: 17.8 x 23.3 x 1.5 cm, minkšti viršeliai
  • Kalba: Anglų

Llmops (el. knyga) (skaityta knyga) | Abi Aryan | knygos.lt

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Learning LLMOps can help optimize the development process, ensure reproducibility, scale infrastructure, and enhance security and privacy, resulting in more efficient and effective deployment of large language models. Large language models require a significant amount of computational resources to develop, train, and fine-tune and can quickly become computationally expensive as the model size and training data increases. LLMOps is an infrastructure management framework that helps scale the infrastructure needed to support these models, making it possible to train and deploy them at scale while ensuring that models are secure and comply with privacy regulations. In this book, you'll learn how to integrate OpenAI ChatGPT and Whisper into your MLOps pipeline to create conversational AI applications. This integration will enable you to build powerful chatbots, virtual assistants, and other conversational AI applications. You'll gain practical experience in developing, deploying, and managing large language models using MLOps techniques.

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  • Autorius: Abi Aryan
  • Leidėjas:
  • ISBN-10: 1098154207
  • ISBN-13: 9781098154202
  • Formatas: 17.8 x 23.3 x 1.5 cm, minkšti viršeliai
  • Kalba: Anglų

Learning LLMOps can help optimize the development process, ensure reproducibility, scale infrastructure, and enhance security and privacy, resulting in more efficient and effective deployment of large language models. Large language models require a significant amount of computational resources to develop, train, and fine-tune and can quickly become computationally expensive as the model size and training data increases. LLMOps is an infrastructure management framework that helps scale the infrastructure needed to support these models, making it possible to train and deploy them at scale while ensuring that models are secure and comply with privacy regulations. In this book, you'll learn how to integrate OpenAI ChatGPT and Whisper into your MLOps pipeline to create conversational AI applications. This integration will enable you to build powerful chatbots, virtual assistants, and other conversational AI applications. You'll gain practical experience in developing, deploying, and managing large language models using MLOps techniques.

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