courseraАнализ данных

Introduction to Transformer Models for NLP: Deploying Modern Models

Курс от Pearson

Средний≈ 4.9 чАнглийский

О курсе

This course covers transformer models and their applications in natural language processing and computer vision. Topics include the T5 model, fine-tuning for tasks such as abstractive summarization, and the Vision Transformer. Students will learn to build an image captioning system by combining vision and language models. The course also provides practical instruction on deploying models, including MLOps practices, sharing models on HuggingFace, and cloud deployment with FastAPI. By the end of the course, students will have the knowledge and skills to implement, fine-tune, and deploy transformer models for various real-world tasks.

Навыки, которые вы освоите

Fine-tuning Model Deployment Vision Transformer (ViT)MLOps (Machine Learning Operations)Generative AI Image Analysis Natural Language Processing Cloud Deployment Large Language Modeling Hugging Face Computer Vision Transfer Learning Generative Model Architectures Application Deployment

Программа курса

1 модулей · 20 учебных материалов

01Introduction to Transformer Models for NLP: Unit 320 материалов

T5 - Back to Basics

TopicsВидео Encoders and decoders welcome: T5-s architectureВидео Cross-attentionВидео T5 - Back to Basics QuizЗадание

Hands-on T5

Учитесь у экспертов

Pearson

Преподаватель курса

Sinan Ozdemir

AI Author, Speaker & Entrepreneur