Semantic Search for AI - Testing Out Qdrant Neural Search

Explore the implementation of semantic search for AI in this comprehensive tutorial video. Learn how to set up a Docker container, create a development environment for machine learning projects, and use cURL on Windows to create collections. Discover techniques for cleaning data using regex, creating search microservices, and setting up a Quadrant client. Delve into the process of installing Sentence Transformers, generating sentence embeddings, and understanding the advantages of using the Google Universal Sentence Encoder. Gain practical insights into testing semantic search engines and enhancing AI-powered search capabilities through hands-on demonstrations and explanations.

- Testing a Semantic Search Engine
- Setting up a Docker Container
- Setting up a development environment for a machine learning project
- Creating a collection with cURL on Windows
- Adding points to Auto Muse
- Cleaning up data for the nexus service
- Using regex to clean up a text file
- Creating a search microservice
- Setting up a Quadrant Client
- Creating a new Quadrant
- Trying to install Sentence Transformers
- Getting sentence embeddings with sentence transformers
- Spooling up sentence embeddings
- The benefits of using the Google Universal Sentence Encoder