LLMs in Practice
Real World Applications, Challenges and Success Stories
by Kiran Jot Singh, Shubham Mahajan, Divneet Singh Kapoor, Khushal Thakur
1st Edition
Publisher: Elsevier
Book Details
| Print ISBN | 9780443443442 |
| eText ISBN | 9780443443459 |
| Publisher | Elsevier |
| Publishing Year | 2026 |
| Edition | 1st Edition |
| Language | English |
| Pages | 540 |
Published by Elsevier, the reference volume *LLMs in Practice* (1st Edition), edited by Kiran Jot Singh, Shubham Mahajan, Divneet Singh Kapoor, and Khushal Thakur, provides cross-disciplinary analysis for applying Large Language Models within healthcare, education, public governance, mental health, creative fields, and intelligent systems. Designed for graduate students, higher undergraduates, researchers, academic audiences, and professional practitioners, the text delivers structured evaluation for real-world deployment.
The material synthesizes key operational methods, focusing on deployment guidance, prompt optimization, and reliability techniques. It further details governance frameworks, risk mitigation tools, and systematic audit strategies to support technical evaluation across organizational settings.
As a focused domain study, the volume examines therapeutic LLMs deployed in mental health through alignment engineering paired with SAFEE-based governance. This focus offers advanced academic programs and industry researchers a clear reference framework for multidisciplinary domain integration.
Table of Contents
Chapter 1: Foundations and Frameworks for Large Language Models: Concepts and Deployment Strategies
Chapter 2: Mathematical Foundations and Reasoning Capabilities of Large Language Models
Chapter 3: Responsibility Gaps in Autonomous Agentic AI: Legal and Ethical Blind Spots in Multi-Agent and Multi-Developer Systems
Chapter 4: Business Transformation and Legal Innovation in the Age of Generative AI
Chapter 5: Policy, Law, and AI in Healthcare: Addressing Legal Hurdles in the Use of Large Language Models
Chapter 6: Enhancing Security and Privacy in the Integration of Large Language Models within Learning Management Systems
Chapter 7: Transforming Healthcare with Large Language Models: Innovation, Integration, and Impact
Chapter 8: Revolutionizing Healthcare Systems Through Large Language Models
Chapter 9: SymptoGuide: Revolutionising Digital Health through Retrieval- Augmented Generation and LLMs
Chapter 10: Enhancing Mental Health and Cognitive Research with Generative AI
Chapter 11: Enhancing Mental Health and Cognitive Research with Generative AI: Transformative Applications, Ethical Considerations, and Future Directions
Chapter 12: Therapeutic LLMs in Mental Health: Evidence, Alignment Engineering, and SAFEE-Based Governance
Chapter 13: Personalized Music-Based Neuro-Rehabilitation Using Generative AI Models
Chapter 14: The Role of Generative AI in Shaping the Future of Mental Health Research
Chapter 15: Financial Services and Risk Intelligence Powered by LLMs
Chapter 16: LLM-Driven Trading: Enhancing Financial Algorithms with Sentiment and Risk Analysis
Chapter 17: Leveraging LLMs for marketing of Financial products for multi-lingual Consumers
Chapter 18: LLM-Driven Marketing Strategy & Consumer Insights
Chapter 19: Leveraging Large Language Models for Intelligent Urban Planning and Smart Cities
Chapter 20: LLMs in Action: Semantic Navigation on TurtleBot4 via MCP-Based Natural Language Interface
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