Learn LangChain in 7 Easy Steps
In this tutorial, I will teach you LangChain as efficiently as possible by breaking down the framework into seven key components you need to understand to start developing more advanced LLM applications.
In this tutorial, I will teach you LangChain as efficiently as possible by breaking down the framework into seven key components you need to understand to start developing more advanced LLM applications.
This tutorial will explore building dashboards using Large Language Models (LLMs) and LangChain. We will use LangChain chains to extract insights from BigQuery by first generating SQL and then pushing the generated SQL to BigQuery as views, forming the basis for interactive dashboards.
This guide helps data analysts, data scientists, and developers leverage LLMs for generating SQL queries from natural language questions, making complex data wrangling in BigQuery and other SQL databases more accessible and intuitive.
Tagging your products systematically is essential in the ecommerce space, as it directly impacts how easily customers can discover and interact with your offerings.
In this tutorial we'll dive into embedding Ecommerce product data, utilizing vector similarity search with Scikit Learn for precise product matching, and doing product retrieval with OpenAI assistants
In this tutorial, we are going to delve into the functionality of OpenAI assistants and how they can be leveraged for extracting data. We will carry out an explicit exercise to extract Shopify data using function calling.
In this tutorial, we'll operationalize Shopify data in Google BigQuery. By leveraging BigQuery, we'll be able to do reporting, support machine learning, and build the foundation for generating insights with Large Language Models (LLMs).
In this tutorial, we'll extract Shopify data efficiently and lay the groundwork for generating insights via LLM-based interfaces.