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Large language models ops for financ...

Jeyaraman, Brindha Priyadarshini.

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Large language models ops for finance = a practical guide to infrastructure, implementation, and innovation /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Large language models ops for finance/ by Brindha Priyadarshini Jeyaraman.
Reminder of title:	a practical guide to infrastructure, implementation, and innovation /
Author:	Jeyaraman, Brindha Priyadarshini.
Published:	Berkeley, CA :Apress : : 2025.,
Description:	xvii, 281 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	Chapter 1: Introduction to Large Language Models in Finance -- Chapter 2: Infrastructure Setup for LLMs -- Chapter 3: Training and Fine-Tuning LLMs -- Chapter 4: Deployment Strategies for LLMs -- Chapter 5: Ensuring Data Privacy and Security -- Chapter 6: Integrating LLMs into Financial Systems -- Chapter 7: Monitoring and Maintenance of LLMs -- Chapter 8: Future Trends in LLM Ops for Finance.
Contained By:	Springer Nature eBook
Subject:	Natural language processing (Computer science) -
Online resource:	https://doi.org/10.1007/979-8-8688-1700-7
ISBN:	9798868817007

Large language models ops for finance = a practical guide to infrastructure, implementation, and innovation /
Jeyaraman, Brindha Priyadarshini.

Large language models ops for financea practical guide to infrastructure, implementation, and innovation /[electronic resource] :by Brindha Priyadarshini Jeyaraman. - Berkeley, CA :Apress :2025. - xvii, 281 p. :ill. (some col.), digital ;24 cm.

Chapter 1: Introduction to Large Language Models in Finance -- Chapter 2: Infrastructure Setup for LLMs -- Chapter 3: Training and Fine-Tuning LLMs -- Chapter 4: Deployment Strategies for LLMs -- Chapter 5: Ensuring Data Privacy and Security -- Chapter 6: Integrating LLMs into Financial Systems -- Chapter 7: Monitoring and Maintenance of LLMs -- Chapter 8: Future Trends in LLM Ops for Finance.

Explore emerging technologies and the evolving role of AI in finance. Geared toward finance professionals, this book will equip you with the knowledge and tools to harness the power of Large Language Models (LLMs), ensuring you stay ahead in an increasingly AI-driven industry. Highlighting the benefits and challenges of LLMs in financial contexts, the book starts with the necessary infrastructure setup, covering both hardware and software requirements. It offers a balanced discussion on cloud versus on-premises solutions, enabling you to make informed decisions based on their specific needs. Training and fine-tuning LLMs are critical components of effective deployment, and this book offers best practices, from data preparation to advanced fine-tuning techniques. It also delves into deployment strategies, with practical advice on building deployment pipelines, monitoring performance, and optimizing operations. Ensuring data privacy and security is paramount in finance, so you'll take a close look at maintaining compliance with regulations while safeguarding sensitive information. You'll also examine the integration of LLMs into existing financial systems, with real-world case studies and strategies for API development and real-time data processing. Monitoring and maintenance are crucial for long-term success, and the book outlines how to manage performance metrics, handle model drift, and ensure regular updates. Large Language Models Ops for Finance is your essential guide to discovering the transformative potential of LLMs in the finance industry.

ISBN: 9798868817007

Standard No.: 10.1007/979-8-8688-1700-7doiSubjects--Topical Terms:

565309
Natural language processing (Computer science)

LC Class. No.: QA76.9.N38 / J49 2025

Dewey Class. No.: 006.35

Large language models ops for finance = a practical guide to infrastructure, implementation, and innovation /
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245 1 0 $a Large language models ops for finance $h [electronic resource] : $b a practical guide to infrastructure, implementation, and innovation / $c by Brindha Priyadarshini Jeyaraman.
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505 0 $a Chapter 1: Introduction to Large Language Models in Finance -- Chapter 2: Infrastructure Setup for LLMs -- Chapter 3: Training and Fine-Tuning LLMs -- Chapter 4: Deployment Strategies for LLMs -- Chapter 5: Ensuring Data Privacy and Security -- Chapter 6: Integrating LLMs into Financial Systems -- Chapter 7: Monitoring and Maintenance of LLMs -- Chapter 8: Future Trends in LLM Ops for Finance.
520 $a Explore emerging technologies and the evolving role of AI in finance. Geared toward finance professionals, this book will equip you with the knowledge and tools to harness the power of Large Language Models (LLMs), ensuring you stay ahead in an increasingly AI-driven industry. Highlighting the benefits and challenges of LLMs in financial contexts, the book starts with the necessary infrastructure setup, covering both hardware and software requirements. It offers a balanced discussion on cloud versus on-premises solutions, enabling you to make informed decisions based on their specific needs. Training and fine-tuning LLMs are critical components of effective deployment, and this book offers best practices, from data preparation to advanced fine-tuning techniques. It also delves into deployment strategies, with practical advice on building deployment pipelines, monitoring performance, and optimizing operations. Ensuring data privacy and security is paramount in finance, so you'll take a close look at maintaining compliance with regulations while safeguarding sensitive information. You'll also examine the integration of LLMs into existing financial systems, with real-world case studies and strategies for API development and real-time data processing. Monitoring and maintenance are crucial for long-term success, and the book outlines how to manage performance metrics, handle model drift, and ensure regular updates. Large Language Models Ops for Finance is your essential guide to discovering the transformative potential of LLMs in the finance industry.
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