Lec 04 | Transformer: Architecture and Training

Описание: Let's dive into the model that changed NLP forever! This lecture, recorded on August 07, 2025, breaks down the groundbreaking Transformer architecture. 🚀 We'll explore its core components, like multi-head self-attention and positional encodings, that allow it to process language with unparalleled effectiveness.

After understanding the architecture, we'll shift our focus to BERT (Bidirectional Encoder Representations from Transformers), examining its revolutionary pre-training and fine-tuning strategies that set a new standard for language understanding tasks.

Resources 📚
For slides and other course materials, please visit the website:
Course Website (lcs2.in/llm2501)

Suggested Readings 📖
Attention Is All You Need (https://proceedings.neurips.cc/paper_...)
The Illustrated Transformer (https://jalammar.github.io/illustrate...)
Transformer Explainer (https://poloclub.github.io/transforme...)
Layer Normalization (https://arxiv.org/pdf/1607.06450)
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (https://arxiv.org/pdf/1810.04805)

#Transformer #BERT #Attention #NLP #DeepLearning #MachineLearning #AI