motovlim

Multi Head Attentionから始まり、Original Transformerモデル、BERT、Encoder-DecoderベースのMarianMT翻訳モデル、Vision Transformerまで、コードで直接実装しながらTransformerについて隅々まで学ぶことができます。

dooleyz3525

신규 강의 오픈 기념 전 강의 30% 할인

実装しながら学ぶTransformer

素敵な受講評ありがとうございます ^^

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transformer

바닥부터구현

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.

입문

초급

중급이상

Deep Learning(DL)

파이토치

PyTorch

encoder-decoder

bert

Learning Transformer Through Implementation

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