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Essential Guide to LLMOps. Implementing effective strategies for Large Language Models in deployment and continuous improvement

(ebook) (audiobook) (audiobook) Książka w języku 1
Autor:
Ryan Doan
Essential Guide to LLMOps. Implementing effective strategies for Large Language Models in deployment and continuous improvement Ryan Doan - okladka książki

Essential Guide to LLMOps. Implementing effective strategies for Large Language Models in deployment and continuous improvement Ryan Doan - okladka książki

Essential Guide to LLMOps. Implementing effective strategies for Large Language Models in deployment and continuous improvement Ryan Doan - audiobook MP3

Essential Guide to LLMOps. Implementing effective strategies for Large Language Models in deployment and continuous improvement Ryan Doan - audiobook CD

Serie wydawnicze:
Beginners Guide
Ocena:
Bądź pierwszym, który oceni tę książkę
Stron:
190
Dostępne formaty:
     PDF
     ePub
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The rapid advancements in large language models (LLMs) bring significant challenges in deployment, maintenance, and scalability. This Essential Guide to LLMOps provides practical solutions and strategies to overcome these challenges, ensuring seamless integration and the optimization of LLMs in real-world applications.
This book takes you through the historical background, core concepts, and essential tools for data analysis, model development, deployment, maintenance, and governance. You’ll learn how to streamline workflows, enhance efficiency in LLMOps processes, employ LLMOps tools for precise model fine-tuning, and address the critical aspects of model review and governance. You’ll also get to grips with the practices and performance considerations that are necessary for the responsible development and deployment of LLMs. The book equips you with insights into model inference, scalability, and continuous improvement, and shows you how to implement these in real-world applications.
By the end of this book, you’ll have learned the nuances of LLMOps, including effective deployment strategies, scalability solutions, and continuous improvement techniques, equipping you to stay ahead in the dynamic world of AI.

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O autorze książki

Ryan, an ex-Amazon Machine Learning Engineer and current VP of Technology at Semantic Health, is a recognized expert in machine learning. A Virginia Tech graduate specializing in robotics and ML, he has applied his skills across diverse sectors, including trading firms, political campaigns, and national security. At Amazon, Ryan contributed significantly to customer experience improvements through ML models and designed systems supporting engineers and scientists. His expertise now fuels ML engineers' training at MLExpert, his unique ML-interview-prep product, sharing his deep industry knowledge and experience with more than 50,000 students.

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