What you'll learn:
- Understand and implement Retrieval-Augmented Generation (RAG) with multimodal data (text, images).
- Build AI-powered search and recommender systems using GPT-4, CLIP, and ChromaDB.
- Generate and utilize text and image embeddings to perform multimodal searches.
- Develop interactive applications with Streamlit to handle user queries and provide AI-driven recommendations
Are you ready to dive into the cutting-edge world of AI-powered search and recommender systems? This course will guide you through the process of building Multimodal Retrieval-Augmented Generation (RAG) systems that combine text and image data for advanced information retrieval and recommendations.
In this hands-on course, you'll learn how to leverage state-of-the-art tools such as GPT-4, CLIP, and ChromaDB to build AI systems capable of processing multimodal data—enhancing traditional search methods with the power of machine learning and embeddings.
What You’ll Learn:
Master Multimodal RAG: Understand the concept of Retrieval-Augmented Generation (RAG) and how to implement it for both text and image-based data.
Build AI-Powered Search & Recommendation Systems: Learn how to construct search engines and recommender systems that can handle multimodal queries, using powerful AI models like GPT-4 and CLIP.
Utilize Embeddings for Cross-Modal Search: Gain practical experience generating and using embeddings to enable search and recommendations based on text or image input.
Develop Interactive Applications with Streamlit: Create user-friendly applications that allow real-time querying and recommendations based on user-provided text or image data.
Key Technologies You'll Work With:
GPT-4: A cutting-edge language model that powers the AI-driven recommendations.
CLIP: An advanced AI model for generating image and text embeddings, making it possible to search images with text.
ChromaDB: A high-performance vector database that enables fast and efficient querying for multimodal embeddings.
Streamlit: A simple yet powerful framework for building interactive web applications.
No prior experience with multimodal systems? No problem!
This course is designed to make advanced AI concepts accessible, with detailed, step-by-step instructions that guide you through each process—from generating embeddings to building complete AI systems. Basic Python knowledge and a curiosity for AI are all you need to get started.
Enroll today and take your AI development skills to the next level by mastering the art of multimodal RAG systems!
