CS 182: Lecture 11: Part 2: Sequence to Sequence
CS 182: Lecture 11: Part 3: Sequence to Sequence
Sequence-to-Sequence (seq2seq) Encoder-Decoder Neural Networks, Clearly Explained!!!
CS 182: Lecture 10: Part 1: Recurrent Neural Networks
Attention for RNN Seq2Seq Models (1.25x speed recommended)
L19.1 Генерация последовательностей с помощью рекуррентных нейронных сетей слов и символов
Encoder-Decoder Architecture for Seq2Seq Models | LSTM-Based Seq2Seq Explained
Mel-спектрограмма и MFCC | Лекция 72 (Часть 1) | Прикладное глубокое обучение
Ilya Sutskever: Sequence to sequence learning with neural networks | NeurIPS 2024 Test of Time Award
Sequence To Sequence Learning With Neural Networks| Encoder And Decoder In-depth Intuition
Word2Vec
Появляется новый тип искусственного интеллекта, и он лучше, чем LLMS?
CS 182: Lecture 12: Part 1: Transformers
Ilya Sutskever: "Sequence to sequence learning with neural networks: what a decade"
LLM fine-tuning или ОБУЧЕНИЕ малой модели? Мы проверили!
Paper Review: Sequence to Sequence Learning with Neural Networks
Архитектура кодера-декодера: обзор
CS 182: Lecture 5: Part 1: Backpropagation
CS 182: Lecture 1, Part 2: Introduction
10. Seq2Seq Models