td-vector-distance
OfficialCalculate vector distances for similarity.
Data & Analytics#semantic search#teradata#text analytics#vector distance#similarity analysis#td_vectordistance
Authorteradata-labs
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This skill automates the calculation of distances between vectors, enabling similarity analysis for tasks like document comparison and semantic search.
Core Features & Use Cases
- Vector Distance Calculation: Computes various distance metrics (Euclidean, Manhattan, Cosine) between sets of vectors.
- Similarity Analysis: Supports use cases such as document similarity, semantic search, and vector analysis.
- Automated Workflow: Provides a complete workflow from data preprocessing to results analysis.
Quick Start
Use the td-vector-distance skill to calculate vector distances for the table named 'my_vectors'.
Dependency Matrix
Required Modules
None requiredComponents
scriptsreferences
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: td-vector-distance Download link: https://github.com/teradata-labs/claude-cookbooks/archive/main.zip#td-vector-distance Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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