Mastering Large Language Models with Python : Unleash the Power of Advanced Natural Language Processing for Enterprise Innovation and Efficiency Using Large Language Models (LLMs) with Python / Raj Arun.

Format:

Book

Author/Creator:

Arun R, Raj, author.

Language:

English

Subjects (All):

Natural language processing (Computer science).

Python (Computer program language).

Physical Description:

1 online resource (352 pages)

Edition:

First edition.

Place of Publication:

Delhi, India : Orange Education Pvt Ltd, [2024]

Summary:

"Mastering Large Language Models with Python" is an indispensable resource that offers a comprehensive exploration of Large Language Models (LLMs), providing the essential knowledge to leverage these transformative AI models effectively. From unraveling the intricacies of LLM architecture to practical applications like code generation and AI-driven recommendation systems, readers will gain valuable insights into implementing LLMs in diverse projects. Covering both open-source and proprietary LLMs, the book delves into foundational concepts and advanced techniques, empowering professionals to harness the full potential of these models. Detailed discussions on quantization techniques for efficient deployment, operational strategies with LLMOps, and ethical considerations ensure a well-rounded understanding of LLM implementation. Through real-world case studies, code snippets, and practical examples, readers will navigate the complexities of LLMs with confidence, paving the way for innovative solutions and organizational growth. Whether you seek to deepen your understanding, drive impactful applications, or lead AI-driven initiatives, this book equips you with the tools and insights needed to excel in the dynamic landscape of artificial intelligence.

Contents:

Cover Page

Title Page

Copyright Page

Dedication Page

About the Author

About the Technical Reviewers

Acknowledgements

Preface

Errata

Table of Contents

1. The Basics of Large Language Models and Their Applications

Introduction

Structure

Introduction to Large Language Models

Unfolding the Journey of Language Models

Influence of Large Language Models

Introducing Transformers and Their Importance

Understanding Transformers

Transformers in Large Language Models

Attention Mechanisms

Add and Norm (Residual Connection and Layer Normalization)

Feed Forward

Masked Multi-Head Attention

Linear and Softmax Layers

Transformers and Large Language Models

Scaling Laws for Large Language Models

KM Scaling Law

Chinchilla Scaling Law

Key Techniques for Large Language Models

Scaling Generated by AI.

Notes:

Description based on publisher supplied metadata and other sources.

Part of the metadata in this record was created by AI, based on the text of the resource.

Description based on print version record.

Includes bibliographical references and index.

ISBN:

9788197081828

8197081824

OCLC:

1430661427