Create Text Embeddings for a Vector Store using LangChain
About this Course
This is a self-paced lab that takes place in the Google Cloud console. In this lab, you learn how to use LangChain to store documents as embeddings in a vector store. You will use the LangChain framework to split a set of documents into chunks, vectorize (embed) each chunk and then store the embeddings in a vector database.Created by: Google Cloud
Related Online Courses
Welcome to \"Requirements Writing\". As the title indicates, over the next four weeks, we will be looking at the important task of writing of text-based requirement statements. The course takes you... more
In this course brought to you by industry leader Check Point, they will cover the Maestro Orchestrator initial installation, creation and configuration of security group via the web user interface... more
This course focuses on the early stages of drug discovery and the identification of promising compounds with which to begin the hunt for a novel drug. Different types of assays and methods are... more
In this course we will examine the aviation and Internet infrastructures, and various policies that have been developed to help guide and strengthen their cybersecurity programs. The aviation and... more
This specialization is for professionals who have heard the buzz around machine learning and want to apply machine learning to data analysis and automation. Whether finance, medicine, engineering,... more
Powered by
