Hands-On AI Engineering: Code First Guide to Building Production Grade LLM Systems with Python | Accompanied with GitHub Tutorials | Learn about Transformers Foundation Models & ML Pipelines - Tapa blanda
Sinopsis
Hands-On AI Engineering is a beginner, code-first guide to building production-grade LLM systems
Written by 4 practicing AI engineers. It focuses on what AI teams deal with every day: performance limits, reliability, evaluation, and cost control.
You’ll learn how to design, build, and operate LLM systems that run efficiently, scale responsibly, and perform under pressure without relying on expensive cloud credits or black-box APIs.
What’s included:
- Training and fine-tuning neural networks with PyTorch
- Parameter-efficient fine-tuning using LoRA and QLoRA on consumer GPUs
- Building robust RAG pipelines (smart chunking, hybrid retrieval, ranking, and faithfulness checks)
- Proper evaluation methods (rubrics, LLM-as-a-judge, golden datasets, regression testing)
- Production realities: monitoring, guardrails, cost optimization, and reliable deployment
Performance add-ons (last chapter)
A companion GitHub repository, carefully sequenced projects you can follow along with and build yourself.
- Project 1 - Simple Companion Chat: Basic chatbot built around a single document.
- Project 2 - Personal Knowledge Q&A: Ask questions over your own files with grounded answers.
- Project 3 - Checked Q&A System: Compare AI answers against expected results.
- Project 4 - Conversational Agent: Multi-turn chat with memory and simple tools.
- Project 5 - Document Summarizer: Controlled summaries with basic quality checks.
- Project 6 - Chapter Explorer: Turn text into outlines and short quizzes.
These projects mirror modern team workflows and give you something concrete to show in interviews or client work.
"Sinopsis" puede pertenecer a otra edición de este libro.
Resultados de la búsqueda para Hands-On AI Engineering: Code First Guide to Building...
Imagen de archivo
Hands-On AI Engineering: Code First Guide to Building Production Grade LLM Systems with Python Accompanied with GitHub Tutorials Learn about Transform
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
Calificación del vendedor: 5 de 5 estrellas
Condición: New. Nº de ref. del artículo: 53655205-n
Comprar nuevo
EUR 30,99
Envío por EUR 2,31
Se envía dentro de Estados Unidos de America
Se envía dentro de Estados Unidos de America
Cantidad disponible: Más de 20 disponibles
Imagen de archivo
Hands-On AI Engineering: Code First Guide to Building Production Grade LLM Systems with Python | Accompanied with GitHub Tutorials | Learn about Transformers Foundation Models & ML Pipelines
Impresión bajo demandaLibrería: California Books, Miami, FL, Estados Unidos de America
Calificación del vendedor: 4 de 5 estrellas
Condición: New. Print on Demand. Nº de ref. del artículo: I-9798252097244
Comprar nuevo
EUR 33,38
Gastos de envío gratis
Se envía dentro de Estados Unidos de America
Se envía dentro de Estados Unidos de America
Cantidad disponible: Más de 20 disponibles
Imagen de archivo
Hands-On AI Engineering: Code First Guide to Building Production Grade LLM Systems with Python Accompanied with GitHub Tutorials Learn about Transform
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
Calificación del vendedor: 5 de 5 estrellas
Condición: As New. Unread book in perfect condition. Nº de ref. del artículo: 53655205
Comprar usado
EUR 35,36
Envío por EUR 2,31
Se envía dentro de Estados Unidos de America
Se envía dentro de Estados Unidos de America
Cantidad disponible: Más de 20 disponibles
Imagen de archivo
Hands-On AI Engineering (Paperback)
Impresión bajo demandaLibrería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de America
Calificación del vendedor: 5 de 5 estrellas
Paperback. Condición: new. Paperback. Hands-On AI Engineering is a beginner, code-first guide to building production-grade LLM systemsWritten by 4 practicing AI engineers. It focuses on what AI teams deal with every day: performance limits, reliability, evaluation, and cost control.You'll learn how to design, build, and operate LLM systems that run efficiently, scale responsibly, and perform under pressure without relying on expensive cloud credits or black-box APIs.What's included: Training and fine-tuning neural networks with PyTorchParameter-efficient fine-tuning using LoRA and QLoRA on consumer GPUsBuilding robust RAG pipelines (smart chunking, hybrid retrieval, ranking, and faithfulness checks)Proper evaluation methods (rubrics, LLM-as-a-judge, golden datasets, regression testing)Production realities: monitoring, guardrails, cost optimization, and reliable deployment Performance add-ons (last chapter)A companion GitHub repository, carefully sequenced projects you can follow along with and build yourself.Project 1 - Simple Companion Chat: Basic chatbot built around a single document.Project 2 - Personal Knowledge Q&A: Ask questions over your own files with grounded answers.Project 3 - Checked Q&A System: Compare AI answers against expected results.Project 4 - Conversational Agent: Multi-turn chat with memory and simple tools.Project 5 - Document Summarizer: Controlled summaries with basic quality checks.Project 6 - Chapter Explorer: Turn text into outlines and short quizzes. These projects mirror modern team workflows and give you something concrete to show in interviews or client work. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9798252097244
Comprar nuevo
EUR 37,68
Gastos de envío gratis
Se envía dentro de Estados Unidos de America
Se envía dentro de Estados Unidos de America
Cantidad disponible: 1 disponibles
Imagen de archivo
Hands-On AI Engineering: Code First Guide to Building Production Grade LLM Systems with Python Accompanied with GitHub Tutorials Learn about Transform
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
Calificación del vendedor: 5 de 5 estrellas
Condición: As New. Unread book in perfect condition. Nº de ref. del artículo: 53655205
Comprar usado
EUR 43,16
Envío por EUR 17,61
Se envía de Reino Unido a Estados Unidos de America
Se envía de Reino Unido a Estados Unidos de America
Cantidad disponible: Más de 20 disponibles
Imagen de archivo
Hands-On AI Engineering: Code First Guide to Building Production Grade LLM Systems with Python Accompanied with GitHub Tutorials Learn about Transform
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
Calificación del vendedor: 5 de 5 estrellas
Condición: New. Nº de ref. del artículo: 53655205-n
Comprar nuevo
EUR 43,51
Envío por EUR 17,61
Se envía de Reino Unido a Estados Unidos de America
Se envía de Reino Unido a Estados Unidos de America
Cantidad disponible: Más de 20 disponibles
Imagen de archivo
Hands-On AI Engineering (Paperback)
Impresión bajo demandaLibrería: CitiRetail, Stevenage, Reino Unido
Calificación del vendedor: 5 de 5 estrellas
Paperback. Condición: new. Paperback. Hands-On AI Engineering is a beginner, code-first guide to building production-grade LLM systemsWritten by 4 practicing AI engineers. It focuses on what AI teams deal with every day: performance limits, reliability, evaluation, and cost control.You'll learn how to design, build, and operate LLM systems that run efficiently, scale responsibly, and perform under pressure without relying on expensive cloud credits or black-box APIs.What's included: Training and fine-tuning neural networks with PyTorchParameter-efficient fine-tuning using LoRA and QLoRA on consumer GPUsBuilding robust RAG pipelines (smart chunking, hybrid retrieval, ranking, and faithfulness checks)Proper evaluation methods (rubrics, LLM-as-a-judge, golden datasets, regression testing)Production realities: monitoring, guardrails, cost optimization, and reliable deployment Performance add-ons (last chapter)A companion GitHub repository, carefully sequenced projects you can follow along with and build yourself.Project 1 - Simple Companion Chat: Basic chatbot built around a single document.Project 2 - Personal Knowledge Q&A: Ask questions over your own files with grounded answers.Project 3 - Checked Q&A System: Compare AI answers against expected results.Project 4 - Conversational Agent: Multi-turn chat with memory and simple tools.Project 5 - Document Summarizer: Controlled summaries with basic quality checks.Project 6 - Chapter Explorer: Turn text into outlines and short quizzes. These projects mirror modern team workflows and give you something concrete to show in interviews or client work. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Nº de ref. del artículo: 9798252097244
Comprar nuevo
EUR 43,52
Envío por EUR 43,44
Se envía de Reino Unido a Estados Unidos de America
Se envía de Reino Unido a Estados Unidos de America
Cantidad disponible: 1 disponibles