YoVDO

Improving Retrieval with RAG Fine-tuning

Offered By: Pluralsight

Tags

Retrieval Augmented Generation (RAG) Courses Machine Learning Courses BERT Courses Multi-Task Learning Courses T5 Courses Domain Adaptation Courses Fine-Tuning Courses Retrieval Augmented Generation Courses

Course Description

Overview

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
Learn effective ways to adapt and optimize RAG models. This course will teach techniques for Fine-tuning RAG models using different methods, such as task-specific, domain adaptation, and multi-task fine-tuning.

Understand how to adapt and optimize RAG models. In this course, Improving Retrieval with RAG Fine-tuning, you’ll gain the ability to fine-tune RAG models using various techniques. First, you’ll explore task-specific fine-tuning using BERT. Next, you’ll discover domain adaptation fine-tuning using GPT. Finally, you’ll learn multi-task fine-tuning using T5. When you finish this course, you’ll have the skills and knowledge to adapt and optimize RAG models for specific domains or datasets.

Syllabus

  • Adapt and Fine-tune RAG models 20mins

Taught by

Dhiraj Kumar

Related Courses

Structuring Machine Learning Projects
DeepLearning.AI via Coursera
Структурирование проектов по машинному обучению
DeepLearning.AI via Coursera
머신 러닝 프로젝트 구조화
DeepLearning.AI via Coursera
Stanford CS330: Deep Multi-Task and Meta Learning
Stanford University via YouTube
Stanford Seminar - The Next Generation of Robot Learning
Stanford University via YouTube