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DeepLearningAI and Weaviate are collaborating on a short course about vector databases, focusing on their applications in LLMs and RAG. The course aims to teach how to use vector databases to gain deeper insights into data, embed multimodal data using ML models, and scale models to handle billions of data points. The course will also cover the origins, limitations, architecture, and open-source tools for RAG. Weaviate is partnering with DeepLearningAI for the course.
We're teaming up with @DeepLearningAI for a short course: Vector Databases - From Embeddings to Applications š Ready to get started with vector databases? Enroll now: https://t.co/RZmFJukuVB https://t.co/BaZSLrUTvL
What is Retrieval-Augmented Generation (RAG)? We will discuss: - The origins of RAG - The LLM's limitations that it tries to fix - Its architecture - Why is it so popular Bonus: A list of open-source tools for RAG implementation! https://t.co/8pPH0qLV3q
On Nov. 14, join our workshop with Weaviate to: š§ Learn how to embed multimodal data using ML models ā±ļø See real-time semantic search in action with vector databases š Scale your models to handle billions of data points using vector databases. RSVP: https://t.co/dQ2XBvgP2m
SHORT COURSE ā Vector #Databases: from Embeddings to Applications: https://t.co/mds9aRT6R4 by @sebawita āāāā #BigData #DataScience #VectorDB #MachineLearning https://t.co/Wifm7hSiD0
Vector databases are a key part of many LLM applications that need search or data retrieval, for example with Retrieval Augmented Generation (RAG). Learn how they work + how to use them in our new short course, taught by @weaviate_io's @sebawita! https://t.co/Yi0mnGt9pE https://t.co/ACuueLLpEk
New short course in collaboration with @weaviate_io: Vector Databases: from Embeddings to Applications. Learn how to use vector databases with LLMs to gain deeper insights into your data, build labs that show how to form embeddings, and more. Join now: https://t.co/eJwWSsKGgG https://t.co/PlYrtKDzBF