Articoli correlati a Mastering Fine-Tuning with LLMs: From Basics to Advanced...
Sinossi
Mastering Fine-Tuning with LLMs: From Basics to Advanced Techniques" provides a comprehensive guide to optimizing large language models (LLMs) for various applications. This book is designed for data scientists, machine learning engineers, and AI enthusiasts who want to harness the power of fine-tuning to enhance LLMs' performance and adapt them to specific tasks.
The book is structured into eight parts, each focusing on different aspects of fine-tuning LLMs. It begins with an introduction to large language models, including their evolution, key concepts, and applications such as natural language understanding, text generation, and conversational AI.
Part II delves into the fundamentals of fine-tuning, covering essential topics like data preparation, setting up the fine-tuning environment, and understanding the differences between pre-training and fine-tuning.
In Part III, the book explores various fine-tuning techniques, including supervised, unsupervised, and self-supervised learning, along with transfer learning and domain adaptation. It provides step-by-step guides and case studies to illustrate how these techniques can be applied in real-world scenarios.
Part IV focuses on advanced fine-tuning strategies, such as hyperparameter tuning, handling imbalanced and limited data, and optimizing training performance. It offers practical advice on managing computational resources and improving efficiency.
Part V addresses evaluating and validating fine-tuned models, discussing evaluation metrics, validation techniques, and error analysis to ensure model reliability and performance.
Part VI covers deployment and maintenance, including strategies for deploying models in production, monitoring performance, and updating models to adapt to new data.
In Part VII, the book delves into ethical considerations and cost management, emphasizing the importance of fairness, transparency, and cost-effective practices in AI development.
Finally, Part VIII presents hands-on projects and case studies, allowing readers to apply their knowledge in practical scenarios. The book concludes with a look at future trends in LLM fine-tuning and the evolving role of LLMs in AI.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
- EditoreIndependently published
- Data di pubblicazione2024
- ISBN 13 9798334013476
- RilegaturaCopertina flessibile
- LinguaInglese
- Numero di pagine94
- Contatto del produttorenon disponibile
Compra nuovo
Visualizza questo articolo
EUR 17,18
EUR 1,96 per la spedizione da U.S.A. a Italia
Destinazione, tempi e costiRisultati della ricerca per Mastering Fine-Tuning with LLMs: From Basics to Advanced...
Foto dell'editore
Mastering Fine-Tuning with LLMs
Print on DemandDa: PBShop.store US, Wood Dale, IL, U.S.A.
Valutazione del venditore 5 su 5 stelle
PAP. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Codice articolo L0-9798334013476
Quantità: Più di 20 disponibili
Foto dell'editore
Mastering Fine-Tuning with LLMs
Print on DemandDa: PBShop.store UK, Fairford, GLOS, Regno Unito
Valutazione del venditore 4 su 5 stelle
PAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Codice articolo L0-9798334013476
Quantità: Più di 20 disponibili
Foto dell'editore
Mastering Fine-Tuning with LLMs: From Basics to Advanced Techniques
Da: Ria Christie Collections, Uxbridge, Regno Unito
Valutazione del venditore 5 su 5 stelle
Condizione: New. In. Codice articolo ria9798334013476_new
Quantità: Più di 20 disponibili
Foto dell'editore
Mastering Fine-Tuning with LLMs: From Basics to Advanced Techniques
Print on DemandDa: California Books, Miami, FL, U.S.A.
Valutazione del venditore 5 su 5 stelle
Condizione: New. Print on Demand. Codice articolo I-9798334013476
Quantità: Più di 20 disponibili
Foto dell'editore
Mastering Fine-Tuning with LLMs: From Basics to Advanced Techniques
Da: GreatBookPrices, Columbia, MD, U.S.A.
Valutazione del venditore 5 su 5 stelle
Condizione: As New. Unread book in perfect condition. Codice articolo 48011411
Quantità: Più di 20 disponibili
Foto dell'editore
Mastering Fine-Tuning with LLMs: From Basics to Advanced Techniques
Da: GreatBookPrices, Columbia, MD, U.S.A.
Valutazione del venditore 5 su 5 stelle
Condizione: New. Codice articolo 48011411-n
Quantità: Più di 20 disponibili
Foto dell'editore
Mastering Fine-Tuning with LLMs: From Basics to Advanced Techniques
Da: GreatBookPricesUK, Woodford Green, Regno Unito
Valutazione del venditore 5 su 5 stelle
Condizione: New. Codice articolo 48011411-n
Quantità: Più di 20 disponibili
Foto dell'editore
Mastering Fine-Tuning with LLMs: From Basics to Advanced Techniques
Da: GreatBookPricesUK, Woodford Green, Regno Unito
Valutazione del venditore 5 su 5 stelle
Condizione: As New. Unread book in perfect condition. Codice articolo 48011411
Quantità: Più di 20 disponibili
Foto dell'editore
Mastering Fine-Tuning with LLMs (Paperback)
Da: CitiRetail, Stevenage, Regno Unito
Valutazione del venditore 5 su 5 stelle
Paperback. Condizione: new. Paperback. Mastering Fine-Tuning with LLMs: From Basics to Advanced Techniques" provides a comprehensive guide to optimizing large language models (LLMs) for various applications. This book is designed for data scientists, machine learning engineers, and AI enthusiasts who want to harness the power of fine-tuning to enhance LLMs' performance and adapt them to specific tasks.The book is structured into eight parts, each focusing on different aspects of fine-tuning LLMs. It begins with an introduction to large language models, including their evolution, key concepts, and applications such as natural language understanding, text generation, and conversational AI.Part II delves into the fundamentals of fine-tuning, covering essential topics like data preparation, setting up the fine-tuning environment, and understanding the differences between pre-training and fine-tuning.In Part III, the book explores various fine-tuning techniques, including supervised, unsupervised, and self-supervised learning, along with transfer learning and domain adaptation. It provides step-by-step guides and case studies to illustrate how these techniques can be applied in real-world scenarios.Part IV focuses on advanced fine-tuning strategies, such as hyperparameter tuning, handling imbalanced and limited data, and optimizing training performance. It offers practical advice on managing computational resources and improving efficiency.Part V addresses evaluating and validating fine-tuned models, discussing evaluation metrics, validation techniques, and error analysis to ensure model reliability and performance.Part VI covers deployment and maintenance, including strategies for deploying models in production, monitoring performance, and updating models to adapt to new data.In Part VII, the book delves into ethical considerations and cost management, emphasizing the importance of fairness, transparency, and cost-effective practices in AI development.Finally, Part VIII presents hands-on projects and case studies, allowing readers to apply their knowledge in practical scenarios. The book concludes with a look at future trends in LLM fine-tuning and the evolving role of LLMs in AI. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Codice articolo 9798334013476
Quantità: 1 disponibili
Foto dell'editore
Mastering Fine-Tuning with LLMs (Paperback)
Da: Grand Eagle Retail, Fairfield, OH, U.S.A.
Valutazione del venditore 5 su 5 stelle
Paperback. Condizione: new. Paperback. Mastering Fine-Tuning with LLMs: From Basics to Advanced Techniques" provides a comprehensive guide to optimizing large language models (LLMs) for various applications. This book is designed for data scientists, machine learning engineers, and AI enthusiasts who want to harness the power of fine-tuning to enhance LLMs' performance and adapt them to specific tasks.The book is structured into eight parts, each focusing on different aspects of fine-tuning LLMs. It begins with an introduction to large language models, including their evolution, key concepts, and applications such as natural language understanding, text generation, and conversational AI.Part II delves into the fundamentals of fine-tuning, covering essential topics like data preparation, setting up the fine-tuning environment, and understanding the differences between pre-training and fine-tuning.In Part III, the book explores various fine-tuning techniques, including supervised, unsupervised, and self-supervised learning, along with transfer learning and domain adaptation. It provides step-by-step guides and case studies to illustrate how these techniques can be applied in real-world scenarios.Part IV focuses on advanced fine-tuning strategies, such as hyperparameter tuning, handling imbalanced and limited data, and optimizing training performance. It offers practical advice on managing computational resources and improving efficiency.Part V addresses evaluating and validating fine-tuned models, discussing evaluation metrics, validation techniques, and error analysis to ensure model reliability and performance.Part VI covers deployment and maintenance, including strategies for deploying models in production, monitoring performance, and updating models to adapt to new data.In Part VII, the book delves into ethical considerations and cost management, emphasizing the importance of fairness, transparency, and cost-effective practices in AI development.Finally, Part VIII presents hands-on projects and case studies, allowing readers to apply their knowledge in practical scenarios. The book concludes with a look at future trends in LLM fine-tuning and the evolving role of LLMs in AI. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Codice articolo 9798334013476
Quantità: 1 disponibili