[{"_1":2,"_3":-5,"_4":-5},"loaderData",{"_5":6,"_7":8},"actionData","errors","root",{"_31":-5,"_56":-5,"_57":58,"_59":60,"_61":62,"_63":64,"_65":66,"_67":68,"_69":70,"_71":72,"_73":74,"_75":76},"routes/_store+/_readers+/email_author.$slug/route",{"_9":10,"_11":-5},"book",{"_12":13,"_14":15,"_16":17,"_18":19,"_20":21,"_22":23},"currentUser","id","Z2lkOi8vbGVhbnB1Yi9TdG9yZTo6Qm9va1Byb2R1Y3QvNjY1NDg","title","Super Study Guide: Transformers y Grandes Modelos de Lenguaje","state","published","contactAuthorMethod","email","aboutText","

Este libro es una guía concisa e ilustrada para cualquiera que desee comprender el funcionamiento interno de los Grandes Modelos de Lenguaje, ya sea de cara a realizar entrevistas, proyectos o para satisfacer su curiosidad.

Está dividido en 5 partes:

Fundamentos: Introducción a las redes neuronales y a los conceptos importantes de aprendizaje profundo para entrenamiento, evaluación y prueba.
Embeddings: Algoritmos de tokenización, embeddings de palabras (word2vec) y embeddings de oraciones (RNN, LSTM, GRU).
Transformers: Motivación detrás de su mecanismo de autoatención, visión detallada de la arquitectura codificador-decodificador y modelos clave relacionados como BERT, GPT y T5.
Grandes Modelos de Lenguaje: Modelos basados en Transformers que logran un rendimiento más avanzado con consejos sobre ingeniería de prompts, junto con cómo hacer ajustes finos (SFT, PEFT) y ajuste por preferencias (RLHF, DPO).
Aplicaciones: Extracción de sentimientos, traducción automática, elaboración de resúmenes, generación aumentada por recuperación y muchas más.

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Kick off your book project in 3 hours! Live workshop on Zoom. You’ll leave with a real book project, progress on your first chapter, and a clear plan to keep going. Saturday, May 16, 2026. Learn more…

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