courseraАнализ данных

Introduction to Transformer Models for NLP: Foundations

Курс от Pearson

Средний≈ 3.4 чАнглийский

О курсе

This course covers the development of natural language processing (NLP), starting with basic concepts and moving to modern transformer architectures. You will learn about attention mechanisms and their impact on language modeling, as well as the details of transformer models, including scaled dot product attention and multi-headed attention. The course includes practical exercises in transfer learning using pre-trained models such as BERT and GPT, with instruction on fine-tuning these models for specific NLP tasks in PyTorch. By the end, you will understand the theory behind current NLP models and gain practical experience in applying them to real-world problems.

Навыки, которые вы освоите

Transfer Learning PyTorch (Machine Learning Library)Natural Language Processing Fine-tuning Generative Model Architectures LLM Application Large Language Modeling

Программа курса

1 модулей · 17 учебных материалов

01Introduction to Transformer Models for NLP: Unit 117 материалов

Module Introduction

Specialization IntroductionВидео

Introduction to Attention and Language Models

TopicsВидео A brief history of NLPВидео Paying attention with attentionВидео

Учитесь у экспертов

Pearson

Преподаватель курса

Sinan Ozdemir

AI Author, Speaker & Entrepreneur