RAG and Fine-Tuning Explained

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Morten Rand-Hendriksen

20:03

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01 - Introduction

01 - RAG, fine-tuning, and the enterprise.mp4

00:48

02 - 1. RAG and Fine-Tuning

01 - How LLMs work.mp4

02:08

02 - Context makes all the difference.mp4

01:21

03 - RAG Retrieval Augmented Generation.mp4

01:46

04 - The RAG flow.mp4

01:30

05 - Embeddings Helping AI understand data.mp4

03:09

06 - Knowledge graphs.mp4

03:16

07 - Fine-tuning.mp4

01:31

08 - RAFT RAG with fine-tuning.mp4

02:04

03 - 2. Conclusion

01 - Tying it all together.mp4

02:30

Description

Successful AI integration in mission-critical systems requires data accuracy. The current best method for this is using Retrieval Augmented Generation (RAG) in combination with fine-tuned language models. In this short course you’ll get a high-level breakdown of how RAG and fine-tuning works, when they are useful, and where pitfalls are for these approaches.

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Artificial Intelligence

Morten Rand-Hendriksen

Instructor's Courses

Since joining forces with lynda.com (now LinkedIn Learning) in 2010, I've 60+ published courses on WordPress, front end web design and development, and web standards, reaching hundreds of thousands of viewers from all over the world. I also contribute to the web community as a public speaker, author, educator, web developer, and design philosopher. I help the web make sense by helping people understand and get the most out of the web, and contribute to the debates about ownership and democratization of information, design philosophy, and the open web.

Linkedin Learning

View courses Linkedin Learning

LinkedIn Learning is an American online learning provider. It provides video courses taught by industry experts in software, creative, and business skills. It is a subsidiary of LinkedIn. All the courses on LinkedIn fall into four categories: Business, Creative, Technology and Certifications. It was founded in 1995 by Lynda Weinman as Lynda.com before being acquired by LinkedIn in 2015. Microsoft acquired LinkedIn in December 2016.