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Data engineering with Python : work with massive datasets to design data models and automate data pipelines using Python

By Crickard, Paul. Birmingham - Mumbai Packt Publishing 2020 . xii, 337p. , Published by Packt Publishing Limited, Birmingham, UK. Title page: Birmingham—Mumbai. 9781839214189 | 183921418X

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Machine learning engineering with Python : manage the production life cycle of machine learning models using MLOps with practical examples

By McMahon, Andrew P.. Birmingham - Mumbai Packt Publishing 2021 . xiv, 260p. , Author: Andrew Peter (Andy) McMahon, PhD, ML Engineering Lead / Head of MLOps, NatWest Group, UK; previously Analytics Team Lead, Aggreko. PhD in Condensed Matter Physics, Imperial College London; BSc Theoretical Physics, University of Glasgow. Named Data Scientist of the Year 2019 (Data Science Foundation) and Rising Star of the Year 2022 (British Data Awards). Co-host of the AI Right podcast. 9781801079259

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Generative AI for cloud solutions : architect modern AI LLMs in secure, scalable, and ethical cloud environments

By Singh, Paul. Birmingham, UK Packt Publishing 2024 . xiii, 275p. 9781835084786

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LLM engineer's handbook : master the art of engineering large language models from concept to production

By Iusztin, Paul. Birmingham, UK Packt Publishing 2024 . xxvi, 490p. , Step into the world of LLMs with this practical guide that takes you from the fundamentals to deploying advanced applications using LLMOps best practices Key Features: - Build and refine LLMs step by step, covering data preparation, RAG, and fine-tuning - Learn essential skills for deploying and monitoring LLMs, ensuring optimal performance in production - Utilize preference alignment, evaluation, and inference optimization to enhance performance and adaptability of your LLM applications 9781836200079 | 1836200072

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Building AI agents with LLMs, RAG, and knowledge graphs : A practical guide to autonomous and modern AI agents

By Raieli, Salvatore . Birmingham, UK Packt Publishing 2025 . xx, 544p, , Master LLM fundamentals to advanced techniques like RAG, reinforcement learning, and knowledge graphs to build, deploy, and scale intelligent AI agents that reason, retrieve, and act autonomously Key Features: - Implement RAG and knowledge graphs for advanced problem-solving - Leverage innovative approaches like LangChain to create real-world intelligent systems - Integrate large language models, graph databases, and tool use for next-gen AI solutions 9781835087060 | 183508706X

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