Qdrant | Storage Engine | Indexing Algorithms | Optimizations | Downsides & Trade-offs | Use Cases
Qdrant is a powerful vector search database designed for high-speed, scalable, and efficient nearst neighbor search over large datasets. It is build for AI, recommendation systems, and RAG-based applications, making it great choice when you need semantic search, image similarity search, and natural language processing (NLP) applications.
Read MoreReady to dive into the world of AI in healthcare? 🚀 In this video, we'll build a powerful medical assistance API called Med Insights, which leverages AI to help doctors diagnose complex cases more efficiently. From data upload to AI-powered querying and generating insightful reports, you'll learn how to create an impactful AI application with Python.
Build an AI-Powered Medical Insights API with Python | Step-by-Step Tutorial #1
Flask vs FastAPI vs Django: Choosing the Best Framework for AI-Powered APIs #2
Master Python Web Servers: WSGI vs ASGI, Uvicorn, Daphne, Hypercorn, uWSGI Simplified! #3
Build an AI-Powered App with FastAPI, Qdrant, NumPy, and Pydantic | Step-by-Step Tutorial #4
Build an AI-Powered App with FastAPI, Qdrant, NumPy, and Pydantic | Step-by-Step Tutorial #5
Build an AI-Powered App with FastAPI, Qdrant, NumPy, and Pydantic | Step-by-Step Tutorial #6
Build an AI-Powered App with FastAPI, Qdrant, NumPy, and Pydantic | Step-by-Step Tutorial #7
Build an AI-Powered App with FastAPI, Qdrant, NumPy, and Pydantic | Step-by-Step Tutorial #8
Build an AI-Powered App with FastAPI, Qdrant, NumPy, and Pydantic | Step-by-Step Tutorial #9
Explore my first video tutorials on building a recommendation system using Python. These videos cover essential tools like AI, PyTorch, and Pandas libraries. While the quality reflects my initial steps in creating tutorials, they provide valuable insights into building intelligent recommendation systems.
PyTorch DataLoader for Recommendation System: Loading and Preparing User-Item Data | Tutorial #1
Building a Recommendation System with Matrix Factorization | Python & PyTorch Tutorial #2
Optimizing PyTorch Recommendation Systems for CPU & GPU | Item Recommendation Tutorial #3
Training & Validating a PyTorch Recommendation Model | Tutorial #4
How to Save and Load Models in PyTorch | Recommendation Systems Tutorial #5
Building a AI, PyTorch Recommendation System | Tutorial #6
How to Build and Run a Neural Network with TensorFlow and Panda – Complete Tutorial