Building a RAG application from scratch using Python, LangChain, and the OpenAI API

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  1. Underfitted
  2. Machine learning
  3. artificial intelligence
  4. data science
  5. software engineering
  6. mlops
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Комментарии
Автор

This will be a great resource! I'd love to see a dedicated video diving deeper into LangGraphs and their applications. Keep up the great work!

cywijdr
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This is the best crispy clear RAG walkthrough that I have seen until now ! Congratulations and thank you for putting effort into educational videos on GenAI use

sgatea
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DUDE!! this is the best resource I have found so far. The part I truly appreciate is that you focused on the conceptual parts and NOT just here is the code

beastunleased
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Love it how you explain everything step by step!

Azam.Rajabov
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Thank you, this is top-notch content!
Many new for me llm rag concepts are clearly explained, and most importantly, it shows how they are interconnected and reinforce each other.

serhiua
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Excellent walk through capturing all the required details

snrajamurugan
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Wow. Great teaching! Explaining the "why" on your lessons, in this case (RAG) is what you dont find in other teaching material . Thank you, this has been very insightful! 👍

salamina_
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Santiago, thank you for the valuable RAG videos. Your insights are well-explained and informative. I would be interested in seeing more of your work on this topic.

TooyAshy-
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Nice - looking forward to dive into this.

Could be nice to see a setup for Application with local LLM for private docs. I think a lot of people are looking for such a video 🤞🏻💪🏻 TY for your Nice work!

Kim-krof
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For me, good mentor is someone that can explain difficult topics with elegant simplicity and you doing it superb! Looking forward to Cohort 12 :)

marcinp
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Genuinely found this to be hyper-valuable, after watching this, tons of concepts now actually make sense to me, Thank you!

samuelwest
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Thanks for taking the effort to explain the concepts one by one.

AdnanAli
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Awesome video with great explanation, step by step with examples, images and code!! Love it.

piclezwd
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I already have experience with Langchain, but wanted to learn more about Pinecone. You are just exceptional at teaching. Thank you so much for this. :)

seallyolme
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Thank you. It is the perfect video when you want start doing RAG just after knowing what RAG is for. Now it is easy to do chatbot for technical documentation queries.

johnnym
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This tutorial was the perfect level of theory + code for a beginner like me to get enough knowledge to start tinkering myself. Subscribed and looking forward to more content!

ImadSyed-gbgg
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Million stars to this video. The content is clear, precise and well explained. Thank you.

tee_iam
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You have sorted most of my understandings for RAG which i was missing here and there, this is your zero shot prompt for me understanding RAG basics Thank You !!

Kidzwish
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Great content! Extremely helpful to get hands-on introduction into LLM and RAG. Thank you!

ddre
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Awesome explanation and content. Your content is by far the best I found on RAG... hats off!👏

grabih