// MODEL OPTIMIZATION AND PROMPT SYNTAX TERM
Data Validation
Data validation is the process of checking if data is accurate, complete, and consistent according to predefined rules and expectations.
TECHNICAL DEFINITION
Data validation is the systematic process of assessing data quality by verifying its adherence to predefined constraints, types, ranges, and business rules, crucial for maintaining data integrity and reliability in ML systems.
BACKGROUND
A large language model (LLM) is a neural network trained on a vast amount of text for natural language processing tasks, especially language generation. LLMs can typically generate, summarize, translate and analyze text in many contexts, and are a foundational technology behind modern chatbots. Biased or inaccurate training data can make an LLM's output less reliable.
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- Data quality checks
- Data integrity
- Data cleansing
- Data verification
USAGE NOTE
Implementing data validation early in the pipeline prevents erroneous data from corrupting models or analyses.