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  • Lingua: Inglese

    Editore: CRC Press, 2026

    1041130813 / 9781041130819

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    Da: California Books, Miami, FL, U.S.A.California Books

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    Condizione: Nuovo

    EUR 83,66

    EUR 2,68 spedizione 
    Spedito in U.S.A.

    Quantità: Più di 20 disponibili

    Condizione: New.

  • Lingua: Inglese

    Editore: CRC Press, 2026

    1041130813 / 9781041130819

    • Brossura

    Da: moluna, Greven, Germaniamoluna

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    Condizione: Nuovo

    EUR 79,84

    EUR 48,99 spedizione 
    Spedito da Germania a U.S.A.

    Quantità: Più di 20 disponibili

    Condizione: New. Uday Kamath has over 25 years of experience in AI product development with a Ph.D. in scalable machine learning. His significant contributions span numerous journals, conferences, books, and patents. Notable books include Large Language Models: A Deep Di.

  • Lingua: Inglese

    Editore: Taylor & Francis Ltd Okt 2026, 2026

    1041130813 / 9781041130819

    • Brossura

    Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH

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    Condizione: Nuovo

    EUR 108,05

    EUR 35,00 spedizione 
    Spedito da Germania a U.S.A.

    Quantità: 2 disponibili

    Taschenbuch. Condizione: Neu. Neuware - Reinforcement learning (RL) has become the engine behind some of the most significant advances in modern artificial intelligence, from defeating world champions in Go to aligning large language models with human preferences. Yet despite its central role, RL remains poorly understood by many practitioners who work with these systems daily. Reinforcement Learning in Action: From Foundations to Frontiers bridges the gap between classical RL theory and the cutting-edge techniques driving today's AI breakthroughs. The book traces a complete path from Markov Decision Processes and Bellman equations through deep RL methods (DQN, REINFORCE, Actor-Critic, PPO) to the modern landscape of LLM alignment (RLHF, DPO, SimPO, KTO), reasoning optimization (GRPO, VinePPO, MCTS), and agentic systems with tool use, memory, and multi-turn planning. A distinguishing feature is the book's consistent five-layer pedagogical structure: each algorithm is presented with its key characteristics, a full mathematical derivation, an honest assessment of its advantages and limitations, a complete from-scratch Python/PyTorch implementation in which variable names match the equations, and a hands-on case study with reproducible experiments. Case studies progress from Grid World navigation and CartPole control to fine-tuning language models with DPO on the HuggingFace ecosystem, training reasoning models with GRPO on mathematical benchmarks, and building a full agentic customer support system. Written for ML engineers, researchers, and advanced students, this book provides both the conceptual depth and implementation fluency needed to understand, build, and extend the RL systems shaping the future of AI.…

  • Lingua: Inglese

    Editore: CRC Press, 2026

    1041131410 / 9781041131410

    • Rilegato

    Da: California Books, Miami, FL, U.S.A.California Books

    Venditore con 5 stelle
    Contatta il venditore

    Condizione: Nuovo

    EUR 194,91

    EUR 2,68 spedizione 
    Spedito in U.S.A.

    Quantità: Più di 20 disponibili

    Condizione: New.

  • Lingua: Inglese

    Editore: CRC Press, 2026

    1041131410 / 9781041131410

    • Rilegato

    Da: moluna, Greven, Germaniamoluna

    Venditore con 5 stelle
    Contatta il venditore

    Condizione: Nuovo

    EUR 179,94

    EUR 48,99 spedizione 
    Spedito da Germania a U.S.A.

    Quantità: Più di 20 disponibili

    Condizione: New. Uday Kamath has over 25 years of experience in AI product development with a Ph.D. in scalable machine learning. His significant contributions span numerous journals, conferences, books, and patents. Notable books include Large Language Models: A Deep Di.

  • Lingua: Inglese

    Editore: Taylor & Francis Ltd Okt 2026, 2026

    1041131410 / 9781041131410

    • Rilegato

    Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH

    Venditore con 5 stelle
    Contatta il venditore

    Condizione: Nuovo

    EUR 240,59

    EUR 35,00 spedizione 
    Spedito da Germania a U.S.A.

    Quantità: 2 disponibili

    Buch. Condizione: Neu. Neuware - Reinforcement learning (RL) has become the engine behind some of the most significant advances in modern artificial intelligence, from defeating world champions in Go to aligning large language models with human preferences. Yet despite its central role, RL remains poorly understood by many practitioners who work with these systems daily. Reinforcement Learning in Action: From Foundations to Frontiers bridges the gap between classical RL theory and the cutting-edge techniques driving today's AI breakthroughs. The book traces a complete path from Markov Decision Processes and Bellman equations through deep RL methods (DQN, REINFORCE, Actor-Critic, PPO) to the modern landscape of LLM alignment (RLHF, DPO, SimPO, KTO), reasoning optimization (GRPO, VinePPO, MCTS), and agentic systems with tool use, memory, and multi-turn planning. A distinguishing feature is the book's consistent five-layer pedagogical structure: each algorithm is presented with its key characteristics, a full mathematical derivation, an honest assessment of its advantages and limitations, a complete from-scratch Python/PyTorch implementation in which variable names match the equations, and a hands-on case study with reproducible experiments. Case studies progress from Grid World navigation and CartPole control to fine-tuning language models with DPO on the HuggingFace ecosystem, training reasoning models with GRPO on mathematical benchmarks, and building a full agentic customer support system. Written for ML engineers, researchers, and advanced students, this book provides both the conceptual depth and implementation fluency needed to understand, build, and extend the RL systems shaping the future of AI.…