User ID:

User ID:

User ID:

User ID:

User ID:

User ID:

User ID:

LLM-Driven Data Engineering Day 2 Lab

Description

In this bonus LLM lab, you will learn how to extend your LLMs capabilities beyond text generation. This includes tasks like sending emails, crafting LinkedIn posts, and exploring the role of agents in aiding you in your technical work such as when bugs arise in your pipeline or database.

Transcript preview: LLM-Driven Data Engineering Day 2 Lab

All right, y'all, welcome to the lab, uh, today should be a pretty interesting time. Uh, we're gonna be going over a couple of different, uh, models and a couple different, uh, lang chain kind of use cases. Um, so hopefully, uh, if y'all haven't done it yet, you'll start here at the read me and you'll see what we need to do here is, uh, I sent y'all that, um, database URL uh Langchain database URL. Um, if you're not watching this live, uh, I have, uh, I have instructions here on how to set up the database URL and set up your own local version of Postgress as well. So that is going to be great, but if you are watching this live, you should check the chat messages and you should be able to just go with me right with the lane chain database URL. And so what we're gonna be working with today is we're gonna be working with um This, uh, kind of set of data here, we have, um, We have a bunch of different tables here. We have like matches, maps, meals, meals, matches, players, all sorts of stuff like that. And you'll see if I say like select star from players. Let's just look at like kind of sample a little bit of this data. You'll see we have like all these different users, these are all different like gamers who are like who have played in. Uh, this is for Halo 5. So like you'll see we have like players and then match details has a player in it.