Designing Large Language Model Applications A Holistic Approach To Llms Suhas Pai by Suhas Pai 9781098150501, 1098150503 instant download after payment.

Large language models (LLMs) have proven themselves to be powerful tools for solving a wide range of tasks, and enterprises have taken note. But transitioning from demos and prototypes to full-fledged applications can be difficult. This book helps close that gap, providing the tools, techniques, and playbooks that practitioners need to build useful products that incorporate the power of language models. Experienced ML researcher Suhas Pai offers practical advice on harnessing LLMs for your use cases and dealing with commonly observed failure modes. You’ll take a comprehensive deep dive into the ingredients that make up a language model, explore various techniques for customizing them such as fine-tuning, learn about application paradigms like RAG (retrieval-augmented generation) and agents, and more. • Understand how to prepare datasets for training and fine-tuning • Develop an intuition about the Transformer architecture and its variants • Adapt pretrained language models to your own domain and use cases • Learn effective techniques for fine-tuning, domain adaptation, and inference optimization • Interface language models with external tools and data and integrate them into an existing software ecosystem

This book is intended for a broad audience, including software engineers transitioning to AI application development, machine learning practitioners and scientists, and product managers. Much of the content in this book is borne from my own experiments with LLMs, so even if you are an experienced scientist, I expect you will find value in it. Similarly, even if you have very limited exposure to the world of AI, I expect you will still find the book useful for understanding the fundamentals of this technology.

The only prerequisites for this book are knowledge of Python coding and an understanding of basic machine learning and deep learning principles. Where required, I provide links to external resources that you can use to sharpen or develop your