9798257184468 - artificial intelligence in production: a practitioner's journey — from transformers and large language models to autonomous agents: 3 di dharmalingam, mr. krishna (6 risultati)
Lingua: Inglese
Editore: Independently published, 2026
- Brossura
Da: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US
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EUR 39,68
Spedizione gratuitaSpedito in U.S.A.Quantità: Più di 20 disponibili
PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
Lingua: Inglese
Editore: Independently published, 2026
- Brossura
Da: PBShop.store UK, Fairford, GLOS, Regno UnitoPBShop.store UK
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EUR 33,71
EUR 6,86 spedizioneSpedito da Regno Unito a U.S.A.Quantità: Più di 20 disponibili
PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
Lingua: Inglese
Editore: Independently Published Apr 2026, 2026
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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EUR 51,00
EUR 64,97 spedizioneSpedito da Germania a U.S.A.Quantità: 2 disponibili
Taschenbuch. Condizione: Neu. Neuware - The third volume of A Practitioner's Journey. Twenty-one chapters cover the modern AI stack end to end - large language models, retrieval-augmented generation, RLHF alignment, autonomous agents, and the LLM-specific infrastructure that surrounds them.
Lingua: Inglese
Editore: Independently published, 2026
- Brossura
- Print on Demand
Da: California Books, Miami, FL, U.S.A.California Books
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EUR 33,77
Spedizione gratuitaSpedito in U.S.A.Quantità: Più di 20 disponibili
Condizione: New. Print on Demand.
Lingua: Inglese
Editore: Independently Published, 2026
- Brossura
- Print on Demand
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail
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EUR 38,19
Spedizione gratuitaSpedito in U.S.A.Quantità: 1 disponibili
Paperback. Condizione: new. Paperback. The third volume of A Practitioner's Journey. Twenty-one chapters cover the modern AI stack end to end - large language models, retrieval-augmented generation, RLHF alignment, autonomous agents, and the LLM-specific infrastructure that surrounds them.This is not another "build a ChatGPT clo…ne" book. It is a working engineer's guide to the techniques and engineering decisions behind production AI systems. You will start with NLP foundations and tokenization, move through transformer architectures and LLMs, build production-grade RAG pipelines with vector stores and reranking, train reward models and align LLMs with RLHF and DPO, and finish with autonomous agents, the Model Context Protocol (MCP), multi-agent coordination, and multi-modal models.You will learn to: Build and deploy production RAG with vector stores, reranking, and citation groundingFine-tune and align LLMs with RLHF, DPO, and Constitutional AIDesign autonomous agent loops with safe tool use and approval gatesCoordinate multiple agents through the Model Context Protocol (MCP)Right-size LLM infrastructure across Bedrock, Vertex, Groq, and on-premDistill large models into deployable, edge-ready footprintsCompanion volumes: Books 1 and 2 of A Practitioner's Journey cover classical ML, deep learning, and the production engineering stack - recommended as prerequisites if you are new to the field, optional if you already work in ML/AI. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Lingua: Inglese
Editore: Independently Published, 2026
- Brossura
- Print on Demand
Da: CitiRetail, Stevenage, Regno UnitoCitiRetail
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 37,89
EUR 43,23 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 1 disponibili
Paperback. Condizione: new. Paperback. The third volume of A Practitioner's Journey. Twenty-one chapters cover the modern AI stack end to end - large language models, retrieval-augmented generation, RLHF alignment, autonomous agents, and the LLM-specific infrastructure that surrounds them.This is not another "build a ChatGPT clo…ne" book. It is a working engineer's guide to the techniques and engineering decisions behind production AI systems. You will start with NLP foundations and tokenization, move through transformer architectures and LLMs, build production-grade RAG pipelines with vector stores and reranking, train reward models and align LLMs with RLHF and DPO, and finish with autonomous agents, the Model Context Protocol (MCP), multi-agent coordination, and multi-modal models.You will learn to: Build and deploy production RAG with vector stores, reranking, and citation groundingFine-tune and align LLMs with RLHF, DPO, and Constitutional AIDesign autonomous agent loops with safe tool use and approval gatesCoordinate multiple agents through the Model Context Protocol (MCP)Right-size LLM infrastructure across Bedrock, Vertex, Groq, and on-premDistill large models into deployable, edge-ready footprintsCompanion volumes: Books 1 and 2 of A Practitioner's Journey cover classical ML, deep learning, and the production engineering stack - recommended as prerequisites if you are new to the field, optional if you already work in ML/AI. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
