SKU/Artículo: AMZ-B0G1PN6GN5

LLMS IN PYTHON : 50+ EXPERT-LEVEL PYTHON PROJECTS FOR MASTERING LARGE LANGUAGE MODELS, LANGCHAIN, AND LANGGRAPH ARCHITECTURES

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Fuera de stock

Peso con empaque:
0.36 kg

Devolución:
No

Condición
Nuevo

Producto de:
Amazon

Sobre este producto

Master the architecture and inner workings of Large Language Models
Build and train LLMs from scratch using modern Python toolchains
Fine-tune and optimize models with LoRA, PEFT, and transfer-learning methods
Create advanced LangChain pipelines for multi-step reasoning and agentic AI
Implement LangGraph for context-aware, structured decision workflows
Design Retrieval-Augmented Generation (RAG) systems that ground LLMs in data
Deploy, scale, and monitor production-grade LLMs in cloud environments
Explore 50+ hands-on projects that reinforce every concept through real-world use cases
Expert-Level Projects: Each project builds on the last, guiding you from fundamental model construction to multi-agent AI design.
Cutting-Edge Frameworks: Covers LangChain, LangGraph, RAG, and modern agentic patterns.
Up-to-Date for 2026: Reflects the latest breakthroughs in LLM architecture, fine-tuning, and open-source tooling.
Engineer’s Perspective: Written by Finn Cordex—an author known for bridging research theory with hands-on, production-grade AI engineering.

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LLMS IN PYTHON : 50+ EXPERT-LEVEL PYTHON PROJECTS FOR MASTERING LARGE LANGUAGE MODELS, LANGCHAIN, AND LANGGRAPH ARCHITECTURES

Compra protegida

Build a Large Language Model (From Scratch)

Hands-On Large Language Models: Language Understanding and Generation

AI Engineering: Building Applications with Foundation Models

LLM Engineer's Handbook: Master the art of engineering large language models from concept to production

Building AI Agents with LLMs, RAG, and Knowledge Graphs: A practical guide to autonomous and modern AI agents

Prompt Engineering for LLMs: The Art and Science of Building Large Language Model-Based Applications

The Agentic AI Bible: The Complete and Up-to-Date Guide to Design, Build, and Scale Goal-Driven, LLM-Powered Agents that Think, Execute and Evolve

The Hundred-Page Language Models Book: hands-on with PyTorch (The Hundred-Page Books)

Building LLMs for Production: Enhancing LLM Abilities and Reliability with Prompting, Fine-Tuning, and RAG

LLMs in Production: From language models to successful products

Knowledge Graphs and LLMs in Action

Large Language Models: A Deep Dive: Bridging Theory and Practice

Build a Large Language Model (From Scratch)

Generative AI with Python: The Developer’s Guide to Pretrained LLMs, Vector Databases, Retrieval Augmented Generation, and Agentic Systems (Rheinwerk Computing)

Generative AI with Python and PyTorch: Navigating the AI frontier with LLMs, Stable Diffusion, and next-gen AI applications

Hands-On Large Language Models: Language Understanding and Generation

Python Natural Language Processing Cookbook: Over 60 recipes for building powerful NLP solutions using Python and LLM libraries

Python, Deep Learning, and LLMs: A Crash Course for Complete Beginners

Generative AI with LangChain: Build production-ready LLM applications and advanced agents using Python, LangChain, and LangGraph