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Quick Start Guide to Large Language Models (LLMs)

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Book Details
Language
English
Publishers
Independently published (11 July 2024)
Weight
0.06 KG
Publication Date
11/07/2024
Pages
34 pages
ISBN-13
9798332828430
Dimensions
15.24 x 0.2 x 22.86 cm
SKU
9798332828430
Author Name
Anand Vemula (Author)
Anand Vemula is a technology, business, ESG and Risk governance Evangelist. He has more than 27 plus years of experience. Has worked in MNC at a CXO level. Has been a part of various projects and forums across customers in BFSI, Healthcare, Retail, Manufacuring, Lifesciences, Energy Industry Verticals. Certified in all the technologies and Enterprise Digital ArchitectRead more about this authorRead less about this author
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"Quick Start Guide to Large Language Models (LLMs)" is a comprehensive manual designed to demystify the complexities of LLMs and equip readers with practical knowledge for leveraging these powerful AI tools. The book serves as an accessible entry point for beginners while providing valuable insights for experienced practitioners looking to deepen their expertise.

The guide begins with a thorough introduction to LLMs, explaining their significance, fundamental concepts, and the wide range of applications they support. From enhancing customer service to driving advancements in healthcare, LLMs have become indispensable across various industries.

Readers are then guided through the initial setup, including prerequisites, environment configuration, and the installation of necessary tools and libraries. This ensures a smooth start for anyone new to working with LLMs.

The core of the book delves into the intricacies of training LLMs. It covers data collection and preparation, emphasizing the importance of high-quality data.

The process of selecting the right model is discussed in detail, followed by a step-by-step guide to training, including best practices to optimize performance and prevent common pitfalls. Fine-tuning is highlighted as a crucial step in tailoring pre-trained models to specific tasks.

Detailed instructions and practical examples are provided to illustrate the fine-tuning process, enabling readers to achieve optimal results with minimal data. The book also addresses the deployment of LLMs, offering insights into various deployment options, integration with applications, and best practices for monitoring and maintenance.

Advanced topics such as transfer learning, handling large datasets, and performance optimization are explored to equip readers with the skills needed to handle complex scenarios. Real-world applications are showcased through case studies and industry-specific use cases, demonstrating the transformative impact of LLMs.

The book concludes with a discussion of future trends and common challenges, providing practical solutions and ethical considerations to guide responsible AI development. Whether you're a novice or an expert, "Quick Start Guide to Large Language Models (LLMs)" offers a clear, concise, and practical pathway to mastering the potential of LLMs.

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