Large Language Models: An Introduction
This book begins with an overview of the Generative AI landscape, distinguishing it from conversational AI and shedding light on the roles of key players like DeepMind and OpenAI. It then reviews the intricacies of ChatGPT, GPT-4, and Gemini, examining their capabilities, strengths, and competitors. Readers will also gain insights into the BERT family of LLMs, including ALBERT, DistilBERT, and XLNet, and how these models have revolutionized natural language processing. Further, the book covers prompt engineering techniques, essential for optimizing the outputs of AI models, and addresses the challenges of working with LLMs, including the phenomenon of hallucinations and the nuances of fine-tuning these advanced models. Designed for software developers, AI researchers, and technology enthusiasts with a foundational understanding of AI, this book offers both theoretical insights and practical code examples in Python. Companion files with code, figures, and datasets are available for downloading from the publisher.
1146274881
Large Language Models: An Introduction
This book begins with an overview of the Generative AI landscape, distinguishing it from conversational AI and shedding light on the roles of key players like DeepMind and OpenAI. It then reviews the intricacies of ChatGPT, GPT-4, and Gemini, examining their capabilities, strengths, and competitors. Readers will also gain insights into the BERT family of LLMs, including ALBERT, DistilBERT, and XLNet, and how these models have revolutionized natural language processing. Further, the book covers prompt engineering techniques, essential for optimizing the outputs of AI models, and addresses the challenges of working with LLMs, including the phenomenon of hallucinations and the nuances of fine-tuning these advanced models. Designed for software developers, AI researchers, and technology enthusiasts with a foundational understanding of AI, this book offers both theoretical insights and practical code examples in Python. Companion files with code, figures, and datasets are available for downloading from the publisher.
54.99 In Stock
Large Language Models: An Introduction

Large Language Models: An Introduction

by Oswald Campesato
Large Language Models: An Introduction

Large Language Models: An Introduction

by Oswald Campesato

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Overview

This book begins with an overview of the Generative AI landscape, distinguishing it from conversational AI and shedding light on the roles of key players like DeepMind and OpenAI. It then reviews the intricacies of ChatGPT, GPT-4, and Gemini, examining their capabilities, strengths, and competitors. Readers will also gain insights into the BERT family of LLMs, including ALBERT, DistilBERT, and XLNet, and how these models have revolutionized natural language processing. Further, the book covers prompt engineering techniques, essential for optimizing the outputs of AI models, and addresses the challenges of working with LLMs, including the phenomenon of hallucinations and the nuances of fine-tuning these advanced models. Designed for software developers, AI researchers, and technology enthusiasts with a foundational understanding of AI, this book offers both theoretical insights and practical code examples in Python. Companion files with code, figures, and datasets are available for downloading from the publisher.

Product Details

ISBN-13: 9781501523298
Publisher: Mercury Learning and Information
Publication date: 09/25/2024
Series: MLI Generative AI Series
Pages: 480
Product dimensions: 6.00(w) x 9.00(h) x 0.90(d)

About the Author

Oswald Campesato (San Francisco, CA) specializes in Deep Learning, Python, Data Science, and
generative AI. He is the author/co-author of over forty books including Google Gemini for Python,
LLMs for Developers, and GPT-4 for Developers (all Mercury Learning).

Table of Contents

1: The Generative AI Landscape
2: ChatGPT and GPT-4
3: LLMs and the BERT Family
4: Prompt Engineering
5: Working with LLMs
6: LLMs and Fine-Tuning
7: SVG and GPT-4
8. Miscellaneous Topics
Index
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