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  • Idioma: Inglés

    Editorial: CRC Press, 2026

    1041130813 / 9781041130819

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    Librería: California Books, Miami, FL, Estados Unidos de AmericaCalifornia Books

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    Condición: Nuevo

    EUR 83,53

    Envío por EUR 2,67 
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    Cantidad disponible: Más de 20 disponibles

    Condición: New.

  • Idioma: Inglés

    Editorial: CRC Press, 2026

    1041130813 / 9781041130819

    • Tapa blanda

    Librería: moluna, Greven, Alemaniamoluna

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    Condición: Nuevo

    EUR 79,84

    Envío por EUR 48,99 
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    Cantidad disponible: Más de 20 disponibles

    Condición: 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.

  • Idioma: Inglés

    Editorial: Taylor & Francis Ltd Okt 2026, 2026

    1041130813 / 9781041130819

    • Tapa blanda

    Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH

    Vendedor de 5 estrellas
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    Condición: Nuevo

    EUR 108,05

    Envío por EUR 35,00 
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    Cantidad disponible: 2 disponibles

    Taschenbuch. Condición: 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.…

  • Idioma: Inglés

    Editorial: CRC Press, 2026

    1041131410 / 9781041131410

    • Tapa dura

    Librería: California Books, Miami, FL, Estados Unidos de AmericaCalifornia Books

    Vendedor de 5 estrellas
    Contactar con el vendedor

    Condición: Nuevo

    EUR 194,60

    Envío por EUR 2,67 
    Se envía dentro de Estados Unidos de America

    Cantidad disponible: Más de 20 disponibles

    Condición: New.

  • Idioma: Inglés

    Editorial: CRC Press, 2026

    1041131410 / 9781041131410

    • Tapa dura

    Librería: moluna, Greven, Alemaniamoluna

    Vendedor de 5 estrellas
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    Condición: Nuevo

    EUR 179,94

    Envío por EUR 48,99 
    Se envía de Alemania a Estados Unidos de America

    Cantidad disponible: Más de 20 disponibles

    Condición: 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.

  • Idioma: Inglés

    Editorial: Taylor & Francis Ltd Okt 2026, 2026

    1041131410 / 9781041131410

    • Tapa dura

    Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH

    Vendedor de 5 estrellas
    Contactar con el vendedor

    Condición: Nuevo

    EUR 240,59

    Envío por EUR 35,00 
    Se envía de Alemania a Estados Unidos de America

    Cantidad disponible: 2 disponibles

    Buch. Condición: 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.…