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What is Data validation?

Data validation is the process of verifying the accuracy, consistency, and integrity of data before its use in analytics, machine learning models, or business processes. It ensures data correctness by detecting errors, inconsistencies, and missing values, improving the reliability of insights derived from datasets.

Efficiently updatable neural network
An efficiently updatable neural network is a machine learning model designed to adapt and learn new data without full retraining. This capability enhances AI applications in areas such as fraud detection, recommendation systems, and real-time analytics by improving efficiency and reducing computational costs.
Test data
Test data refers to datasets used to evaluate the performance and accuracy of machine learning models. It is separate from training data and ensures that AI systems generalize well to new, unseen data.
Genetic privacy
Genetic privacy refers to the protection of an individual’s genomic data from unauthorized access, misuse, or exploitation. Privacy laws and ethical guidelines regulate how genetic data is collected, stored, and shared in medical research, ancestry testing, and law enforcement applications to prevent discrimination and ensure data security.

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