Building Applications with Large Language Models: Techniques, Implementation, and Applications

Author:   Bhawna Singh
Publisher:   APress
ISBN:  

9798868805684


Pages:   280
Publication Date:   30 November 2024
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Building Applications with Large Language Models: Techniques, Implementation, and Applications


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Author:   Bhawna Singh
Publisher:   APress
Imprint:   APress
ISBN:  

9798868805684


Pages:   280
Publication Date:   30 November 2024
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Chapter 1: Introduction to Large Language Models.- Chapter 2: Understanding Foundation Models.- Chapter 3: Adapt with Fine-tuning.- Chapter 4: The Magic of Prompt Engineering.- Chapter 5: Stop Hallucination with RAG.- Chapter 6: Evaluation of LLM.- Chapter 7: Tools and Frameworks for Development.- Chapter 8: Run in Production.-Chapter 9: The Ethical Dilemma.- Chapter 10: Future of AI.

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Author Information

Bhawna Singh, a Data Scientist at CeADAR (UCD), holds both a bachelor and master degree in computer science. During her master’s program, she conducted research focused on identifying gender bias in Energy Policy data across the European Union. With prior experience as a Data Scientist at Brightflag in Ireland and a Machine Learning Engineer at AISmartz in India, Bhawna brings a wealth of expertise from both industry and academia. Her current research interests center on exploring diverse applications of Large Language Models. Over the course of her career, Bhawna has built models on extensive datasets, contributing to the development of intelligent systems addressing challenges such as customer churn, propensity prediction, sales forecasting, recommendation engines, customer segmentation, pdf validation, and more. She is dedicated to creating AI systems that are accessible to everyone, promoting inclusivity regardless of race, gender, social status, or language.

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