Our RAG live course is coming up soon, and as a way of giving back to our amazing community, we're offering you 15% off. Just use this link: maven.com/angelina-yang/mastering-rag-systems-a-hands-on-guide-to-production-ready-ai?promoCode=TwoSetAI We'd love to see you there! 🎉 In the course, you'll have the chance to connect directly with Professor Mehdi (just like I do 😉 in the videos), and you can even ask him your questions 1:1. Bring your real work projects, and during our office hours, we'll help you tackle your day-to-day challenges. This course is for: 01 👇 𝗔𝗜 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝘀 & 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿𝘀: For AI engineers/developers looking to master production-ready RAG systems combining search with AI models. 02 👇 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝘁𝗶𝘀𝘁𝘀: Ideal for data scientists seeking to expand into AI by learning hands-on RAG techniques for real-world applications. 03 👇 𝗧𝗲𝗰𝗵 𝗟𝗲𝗮𝗱𝘀 & 𝗣𝗿𝗼𝗱𝘂𝗰𝘁 𝗠𝗮𝗻𝗮𝗴𝗲𝗿𝘀: Perfect for tech leads/product managers wanting to guide teams in building and deploying scalable RAG systems
Amazing video! A followup question: regarding the judge who decide 0 or 1, what if the judge is incorrect? Any methods about how can we make this role robust enough? Thx!
Great question! Your judge should be really capable i.e. GPT4o or specialized LLM models for this task. However, even they could potentially make mistakes. Even if judge does miss, what is the worst that can happen? it does an online search and use it to answer the question. So nothing bad will happen. That said, You must evaluate your judge decisions and improve it if necessary!
![กี่หมื่นฟ้า | Your Sky Series EP.1 [2/4]](http://i.ytimg.com/vi/qJbQs_nhjD4/mqdefault.jpg)
![กี่หมื่นฟ้า | Your Sky Series EP.1 [1/4]](http://i.ytimg.com/vi/vLGjxFL6U_I/mqdefault.jpg)
Our RAG live course is coming up soon, and as a way of giving back to our amazing community, we're offering you 15% off. Just use this link: maven.com/angelina-yang/mastering-rag-systems-a-hands-on-guide-to-production-ready-ai?promoCode=TwoSetAI
We'd love to see you there! 🎉
In the course, you'll have the chance to connect directly with Professor Mehdi (just like I do 😉 in the videos), and you can even ask him your questions 1:1. Bring your real work projects, and during our office hours, we'll help you tackle your day-to-day challenges.
This course is for:
01 👇
𝗔𝗜 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝘀 & 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿𝘀: For AI engineers/developers looking to master production-ready RAG systems combining search with AI models.
02 👇
𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝘁𝗶𝘀𝘁𝘀: Ideal for data scientists seeking to expand into AI by learning hands-on RAG techniques for real-world applications.
03 👇
𝗧𝗲𝗰𝗵 𝗟𝗲𝗮𝗱𝘀 & 𝗣𝗿𝗼𝗱𝘂𝗰𝘁 𝗠𝗮𝗻𝗮𝗴𝗲𝗿𝘀: Perfect for tech leads/product managers wanting to guide teams in building and deploying scalable RAG systems
Awesome video as usual. Can't wait to do the course.
The course is already out. here's the link:
maven.com/angelina-yang/mastering-rag-systems-a-hands-on-guide-to-production-ready-ai
Excellent tutorial , and in very informative and simple language, can you please share the code with us.
Thank you! Here's the code: github.com/mallahyari/twosetai/blob/main/13_agentic_rag.ipynb
Its in the video description now!
Amazing video! A followup question: regarding the judge who decide 0 or 1, what if the judge is incorrect? Any methods about how can we make this role robust enough? Thx!
Great question! Your judge should be really capable i.e. GPT4o or specialized LLM models for this task. However, even they could potentially make mistakes. Even if judge does miss, what is the worst that can happen? it does an online search and use it to answer the question. So nothing bad will happen. That said, You must evaluate your judge decisions and improve it if necessary!
Amazing video
this kind of teacher we need rather who teach abscration plz make more video on complex topics with is man tq
Thanks for sharing great explanation on Agentic AI
Excellent explanation thx ! :)