During training, the model is fed processed data and iteratively learns patterns by adjusting its weights. Optimization techniques like gradient descent and backpropagation are used to fine-tune model parameters. This phase is where the model learns from the data.
This is the text view of an interactive 3D knowledge graph — open this page with JavaScript enabled to explore it visually.
🧠 Knowledge Graph
👁 read-only snapshot
Select a node
The owner's editing tools — shown here so you can see how the graph is grown, but read-only.
Click a bubble to drill in · click again to collapse · drag to orbit
Quiz
Proposed changes
⚠️ Includes destructive changes (merge/delete). They can still be reverted with Undo after applying.
🔒 Only the owner can edit this graph
You're browsing a read-only snapshot. The editing tools are shown so you can see how the graph is grown, but changes are disabled here — exploring, searching and path-finding all work.