The Two-Tower Model
Embed users and items into the same vector space. This allows for lightning-fast Approximate Nearest Neighbor (ANN) search during the retrieval phase.
Ranking Models
Once 1,000 candidates are retrieved, use a heavier model (like a Deep Cross Network or just XGBoost) to re-rank them based on dense, real-time features before serving top 10 to the user.
Internal Resources
- Inference Cost Calculator
- Latency Estimator
- Tabular vs Deep Learning
- Local LLMs vs Managed APIs
- Time Series Baselines
- Tabular Model Selector
- Vision Architecture Selector
- VRAM Calculator
- Choosing Embeddings
- CNN vs ViT in 2024
- RLHF vs DPO
- RAG Chunking Strategies
- RAG Chunk Size Calculator
- Token Ratio Estimator
- Synthetic Data Generation
- Quantization Methods Explained
- Quantization Memory Savings
- Fine-Tuning vs LoRA
- LoRA Rank Calculator
- Multimodal Model Landscape