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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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Generative adversarial networks cookbook : over 100 recipes to build generative models using Python, TensorFlow, and Keras

By Kalin, Josh. Birmingham, UK Packt Publishing 2018 . viii, 252p. 9781789139907 | 1789139902

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Mastering reinforcement learning with Python build next-generation, self-learning models using reinforcement learning techniques and best practices

By Bilgin, Enes. Birmingham, UK Packt Publishing 2020 . xvi, 525p. , Get hands-on experience in creating state-of-the-art reinforcement learning agents using TensorFlow and RLlib to solve complex real-world business and industry problems with the help of expert tips and best practices Key Features: Understand how large-scale state-of-the-art RL algorithms and approaches work Apply RL to solve complex problems in marketing, robotics, supply chain, finance, cybersecurity, and more Explore tips and best practices from experts that will enable you to overcome real-world RL challenges | This book is for expert machine learning practitioners and researchers looking to focus on hands-on reinforcement learning with Python by implementing advanced deep reinforcement learning concepts in real-world projects. Reinforcement learning experts who want to advance their knowledge to tackle large-scale and complex sequential decision-making problems will also find this book useful. Working knowledge of Python programming and deep learning along with prior experience in reinforcement learning is required. 9781838644147 | 1838644148

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