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Decoding Large Language Models. An exhaustive guide to understanding, implementing, and optimizing LLMs for NLP applications

Język publikacji: 1
Autor:
Irena Cronin
Decoding Large Language Models. An exhaustive guide to understanding, implementing, and optimizing LLMs for NLP applications Irena Cronin - okladka książki

Decoding Large Language Models. An exhaustive guide to understanding, implementing, and optimizing LLMs for NLP applications Irena Cronin - okladka książki

Serie wydawnicze:
Other Role Guide
Ocena:
Bądź pierwszym, który oceni tę książkę
Stron:
396
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Ever wondered how large language models (LLMs) work and how they're shaping the future of artificial intelligence? Written by a renowned author and AI, AR, and data expert, Decoding Large Language Models is a combination of deep technical insights and practical use cases that not only demystifies complex AI concepts, but also guides you through the implementation and optimization of LLMs for real-world applications.
You’ll learn about the structure of LLMs, how they're developed, and how to utilize them in various ways. The chapters will help you explore strategies for improving these models and testing them to ensure effective deployment. Packed with real-life examples, this book covers ethical considerations, offering a balanced perspective on their societal impact. You’ll be able to leverage and fine-tune LLMs for optimal performance with the help of detailed explanations. You’ll also master techniques for training, deploying, and scaling models to be able to overcome complex data challenges with confidence and precision. This book will prepare you for future challenges in the ever-evolving fields of AI and NLP.
By the end of this book, you’ll have gained a solid understanding of the architecture, development, applications, and ethical use of LLMs and be up to date with emerging trends, such as GPT-5.

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O autorze książki

Irena Cronin is the CEO of Infinite Retina, a company based in Pasadena, California that helps businesses enter and succeed in Spatial Computing. She has advised many decision-makers on business strategies related to Spatial Computing which includes AR/VR, Artificial Intelligence, Facial Recognition, Robotics, Autonomous Vehicles, and other related technologies.

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