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Vector search and Weaviate
Weaviate · vector search, rag, embeddings, hybrid search
AI directory search
Use this when you know the topic you need: Claude Code, MCP, evals, RAG, agents, product, coding, prompting, foundations, or model internals.
22 matches for "embeddings"
The Illustrated Transformer · Beginner to intermediate
Still one of the clearest visual explanations of transformer concepts.
Skills
Transformers, Embeddings, LLM concepts
James Briggs AI tutorials · Beginner to intermediate
Useful practical explanations of embeddings, retrieval, LangChain, Pinecone, and agent workflows.
Skills
Vector search, RAG, Agents, Embeddings
Sentence Transformers · Intermediate
Essential education for understanding sentence embeddings and semantic search in practice.
Skills
Embeddings, Semantic search, Vector search, NLP
A fast, practical way to build vocabulary and intuition before going deeper into LLMs or AI engineering.
Topics
ML foundations, Classification, Embeddings, Neural networks
Pinecone Learn · Beginner to advanced
Useful for understanding vector search, embeddings, chunking, retrieval, and RAG system design.
Topics
Vector databases, RAG, Embeddings, Search
Weaviate Academy · Beginner to intermediate
Good structured learning around vector databases, retrieval, and search relevance.
Topics
Vector search, RAG, Hybrid search, Embeddings
Natural Language Processing with Deep Learning · Intermediate to advanced
A deep route into the NLP concepts behind embeddings, attention, and modern language models.
Topics
NLP, Transformers, Embeddings, Language models
Qdrant Learning Center · Beginner to intermediate
Good for vector search concepts and practical retrieval implementation.
Topics
Vector search, RAG, Embeddings, Search
Chroma docs · Beginner to intermediate
Useful for fast local experiments with embeddings and retrieval.
Topics
Vector search, RAG, Embeddings, Local apps
Milvus tutorials · Intermediate
Good for learning vector database concepts and scaling retrieval systems.
Topics
Vector databases, RAG, Embeddings, Search
Cohere model docs · Beginner to advanced
Official material for learning Cohere chat, embedding, rerank, and LLM University material, especially for grounded enterprise retrieval workflows.
Topics
Command models, RAG, Embeddings, Reranking, Enterprise AI, Model selection, Course material
Perplexity API docs · Beginner to advanced
Official material for learning web-grounded AI search, Sonar, Agent API workflows, citations, MCP-server access, retrieval, and model choice.
Topics
AI search, Sonar, Agent API, Grounded answers, Model selection, Research workflows, MCP
Free tutorial · Matt Pocock · Beginner to intermediate
You want to build TypeScript LLM apps with Vercel's AI SDK, including streaming, structured outputs, model switching, embeddings, tool calls, and agents.
ai sdk, typescript, streaming, structured outputs, tool calling
Model docs · Cohere · Beginner to advanced
You need to choose between current Cohere Command, embedding, and rerank models for grounded enterprise search.
cohere, command, rag, embeddings, reranking
Model catalog · Qwen · Intermediate
You need the current hosted Qwen and third-party model catalog with modality coverage and capability splits.
qwen, model selection, multimodal, reranking, embeddings
API docs · Perplexity · Beginner to advanced
You need to understand Search, Sonar, Agent, and Embeddings APIs for grounded AI research workflows.
perplexity, sonar, agent api, ai search, grounded answers
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Guide · Pinecone · Beginner to intermediate
You need to understand the moving parts of RAG.
rag, vector search, embeddings
Visual essays · Jay Alammar · Beginner to intermediate
Use this when you want Jay Alammar's material for transformers and related AI skills.
Transformers, Embeddings, LLM concepts
YouTube tutorials · James Briggs · Beginner to intermediate
Use this when you want James Briggs's material for vector search and related AI skills.
Vector search, RAG, Agents, Embeddings
Docs · Nils Reimers · Intermediate
Use this when you want Nils Reimers's material for embeddings and related AI skills.
Embeddings, Semantic search, Vector search, NLP