Building Reliable AI Systems (MEAP 11) by Rush Shahani (.ePUB)+
File Size: 24.3 MB
Building Reliable AI Systems (MEAP 11) by Rush Shahani
Requirements: .ePUB, .PDF reader, 24.3 MB
Overview: Tested strategies to reduce hallucinations, improve performance and cost efficiency, and reduce bias or unethical behavior in your LLMs outputs. Building Reliable AI Systems shows you exactly how to guide large language models from research prototypes to scalable, robust, and efficient production systems. From model training to maintenance, an engineer will find everything they need to work with LLMs in this one-stop guide. This book complements Sebastian Raschka’s Build a Large Language Model (From Scratch), which takes a hands-on, ground-up approach to constructing LLMs. While Raschka’s book focuses on building models from scratch, Building Reliable AI Systems centers on deploying, optimizing, and maintaining reliable, production-grade AI systems. This book will guide you through the entire process, from mitigating hallucinations and reducing bias to optimizing performance and ensuring reliability in LLM-powered applications. You’ll dive into advanced topics like prompt engineering, creating intelligent agents, and the powerful technique of Retrieval-Augmented Generation (RAG). But this isn’t just theory—each chapter includes real-world examples and projects that demonstrate how to put these concepts into action. For data scientists or software engineers confident in Python and NLP.
Genre: Non-Fiction > Tech & Devices
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