Multimodal AI Systems Engineering: Building Production Vision-Language Models, Document AI, and Cross-Modal Retrieval Pipelines - Brossura
Libro 9 di 11: Production AI Engineering Series
Sinossi
Master the Production Lifecycle of Vision-Language Models
The gap between a simple VLM demo and a highly reliable, cost-effective production system is enormous. Multimodal AI Systems Engineering bridges this gap, providing ML engineers, AI platform architects, and computer vision specialists with the definitive blueprint for deploying multimodal AI at enterprise scale.
This comprehensive, hands-on guide skips the high-level hype and dives straight into the concrete architectures, optimization pipelines, and serving infrastructure required to run models like LLaVA, SigLIP, and Qwen-VL in production environments.
What you will master inside this book:- Core Architectures: Deep dive into CLIP, ViT, SigLIP, and modern vision-language models (VLMs).
- Multimodal RAG Pipelines: Design cross-modal embedding spaces, joint vector stores, and advanced retrieval pipelines.
- Inference Optimization: Implement quantization, ONNX, TensorRT, and continuous batching to slash latency and costs.
- Document AI & Vision: Build robust extraction pipelines for OCR, layout detection, form processing, and temporal video modeling.
- Fine-Tuning & Serving: Scale training with LoRA, QLoRA, and DPO, and serve models with NVIDIA Triton Server.
- Enterprise Evaluation: Rigorously evaluate and monitor VLMs using standardized benchmarks and automated CI/CD evaluation loops.
Whether you are building next-generation Document AI pipelines, complex cross-modal search engines, or deploying fine-tuned VLMs onto edge devices, this book delivers the battle-tested engineering patterns you need to succeed in the real world.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Risultati della ricerca per Multimodal AI Systems Engineering: Building Production...
Foto dell'editore
Multimodal AI Systems Engineering: Building Production Vision-Language Models, Document AI, and Cross-Modal Retrieval Pipelines (Production AI Engineering Series)
Print on DemandDa: California Books, Miami, FL, U.S.A.
Valutazione del venditore 4 su 5 stelle
Condizione: New. Print on Demand. Codice articolo I-9798180602398
Compra nuovo
EUR 13,56
Spedizione gratuita
Spedito in U.S.A.
Spedito in U.S.A.
Quantità: Più di 20 disponibili
Foto dell'editore
Multimodal AI Systems Engineering
Da: PBShop.store US, Wood Dale, IL, U.S.A.
Valutazione del venditore 5 su 5 stelle
PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000. Codice articolo L2-9798180602398
Compra nuovo
EUR 14,16
Spedizione gratuita
Spedito in U.S.A.
Spedito in U.S.A.
Quantità: Più di 20 disponibili
Foto dell'editore
Multimodal AI Systems Engineering
Da: PBShop.store UK, Fairford, GLOS, Regno Unito
Valutazione del venditore 5 su 5 stelle
PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000. Codice articolo L2-9798180602398
Compra nuovo
EUR 13,53
Spedizione EUR 3,85
Spedito da Regno Unito a U.S.A.
Spedito da Regno Unito a U.S.A.
Quantità: Più di 20 disponibili
Foto dell'editore
Multimodal AI Systems Engineering (Paperback)
Print on DemandDa: CitiRetail, Stevenage, Regno Unito
Valutazione del venditore 5 su 5 stelle
Paperback. Condizione: new. Paperback. Master the Production Lifecycle of Vision-Language ModelsThe gap between a simple VLM demo and a highly reliable, cost-effective production system is enormous. Multimodal AI Systems Engineering bridges this gap, providing ML engineers, AI platform architects, and computer vision specialists with the definitive blueprint for deploying multimodal AI at enterprise scale.This comprehensive, hands-on guide skips the high-level hype and dives straight into the concrete architectures, optimization pipelines, and serving infrastructure required to run models like LLaVA, SigLIP, and Qwen-VL in production environments.What you will master inside this book: Core Architectures: Deep dive into CLIP, ViT, SigLIP, and modern vision-language models (VLMs).Multimodal RAG Pipelines: Design cross-modal embedding spaces, joint vector stores, and advanced retrieval pipelines.Inference Optimization: Implement quantization, ONNX, TensorRT, and continuous batching to slash latency and costs.Document AI & Vision: Build robust extraction pipelines for OCR, layout detection, form processing, and temporal video modeling.Fine-Tuning & Serving: Scale training with LoRA, QLoRA, and DPO, and serve models with NVIDIA Triton Server.Enterprise Evaluation: Rigorously evaluate and monitor VLMs using standardized benchmarks and automated CI/CD evaluation loops.Whether you are building next-generation Document AI pipelines, complex cross-modal search engines, or deploying fine-tuned VLMs onto edge devices, this book delivers the battle-tested engineering patterns you need to succeed in the real world. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Codice articolo 9798180602398
Compra nuovo
EUR 16,88
Spedizione EUR 43,35
Spedito da Regno Unito a U.S.A.
Spedito da Regno Unito a U.S.A.
Quantità: 1 disponibili
Foto dell'editore
Multimodal AI Systems Engineering : Building Production Vision-Language Models, Document AI, and Cross-Modal Retrieval Pipelines
Da: AHA-BUCH GmbH, Einbeck, Germania
Valutazione del venditore 5 su 5 stelle
Taschenbuch. Condizione: Neu. Neuware - Master the Production Lifecycle of Vision-Language ModelsThe gap between a simple VLM demo and a highly reliable, cost-effective production system is enormous. Multimodal AI Systems Engineering bridges this gap, providing ML engineers, AI platform architects, and computer vision specialists with the definitive blueprint for deploying multimodal AI at enterprise scale.This comprehensive, hands-on guide skips the high-level hype and dives straight into the concrete architectures, optimization pipelines, and serving infrastructure required to run models like LLaVA, SigLIP, and Qwen-VL in production environments.What you will master inside this book: - Core Architectures: Deep dive into CLIP, ViT, SigLIP, and modern vision-language models (VLMs).- Multimodal RAG Pipelines: Design cross-modal embedding spaces, joint vector stores, and advanced retrieval pipelines.- Inference Optimization: Implement quantization, ONNX, TensorRT, and continuous batching to slash latency and costs.- Document AI & Vision: Build robust extraction pipelines for OCR, layout detection, form processing, and temporal video modeling.- Fine-Tuning & Serving: Scale training with LoRA, QLoRA, and DPO, and serve models with NVIDIA Triton Server.- Enterprise Evaluation: Rigorously evaluate and monitor VLMs using standardized benchmarks and automated CI/CD evaluation loops.Whether you are building next-generation Document AI pipelines, complex cross-modal search engines, or deploying fine-tuned VLMs onto edge devices, this book delivers the battle-tested engineering patterns you need to succeed in the real world. Codice articolo 9798180602398
Compra nuovo
EUR 14,00
Spedizione EUR 60,69
Spedito da Germania a U.S.A.
Spedito da Germania a U.S.A.
Quantità: 2 disponibili