How to build an Image Similarity Search app with Image Embeddings & Qdrant

In this video, I'll show you how to use ResNet's Image Model to convert a dataset of images into a series of embeddings (or vectors!), that we can then upload to a vector database - we'll be using Qdrant Cloud. From there, we can then query our embeddings using our database; we can even search for similar records! What we'll cover === 🔎 Sourcing an image dataset (We'll be using Kaggle to fetch ours) 🌆 Image Embeddings (We'll use Microsoft's ResNet 50 Model) 📊 Vector Databases (We'll use Qdrant Cloud to host our data!) 💻 Streamlit (for the frontend of our app) Timestamps === 0:00 Introduction 0:28 What are we building? 0:58 How will we build it? 3:01 Converting our images to embeddings 16:49 Uploading our embeddings to the vector database 22:30 Building the frontend with Streamlit 35:59 Outtro