I have taken several online courses on Transformers, and this one is the most detailed. Thank you for always providing such thorough explanations.

jsmak6174

From Multi-Head Attention to the Original Transformer model, BERT, the Encoder-Decoder based MarianMT translation model, and even Vision Transformer, you'll learn Transformer inside and out by implementing them directly in code.

dooleyz3525

Learning Transformer Through Implementation

Oh, thank you for the great review. Since the Transformer can be difficult for those encountering it for the first time, some parts of the explanation might have been a bit excessive. I will keep that in mind when creating the next lecture.

이론과 실습 한 번에

이론 실습 모두

transformer

바닥부터구현

입문

초급

중급이상

Deep Learning(DL)

파이토치

PyTorch

encoder-decoder

bert

Course Introduction and Lab Environment Setup

Prerequisite Knowledge for Transformer - Understanding NLP Foundations and RNNs

Transformer Overview and Multi-Head Self-Attention Implementation

Transformer Encoder Implementation

Transformer Decoder Implementation

Handling Hugging Face Datasets

Handling Hugging Face Tokenizer and DataCollator

BERT Model Implementation, Training, and Inference

Implementation of the MarianMT Encoder-Decoder Translation Model

Training and Inference of the Implemented MarianMT Model

Vision Transformer (ViT) Implementation