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What is Data labeling?

Data labeling is the process of tagging raw data with meaningful annotations to enable machine learning models to recognize patterns. It is crucial in supervised learning applications such as image recognition, NLP, and speech processing.

Data security
Data security encompasses strategies, policies, and technologies designed to protect digital information from unauthorized access, breaches, and cyber threats. It includes encryption, access controls, firewalls, and threat monitoring to ensure data integrity, confidentiality, and availability across networks and storage systems.
Economics of open data
Economics of open data examines the financial and societal impact of freely accessible public data. It explores how governments, businesses, and researchers can leverage open datasets to drive innovation, improve decision-making, and enhance public services, while also addressing concerns around privacy, monetization, and regulatory challenges.
Data verification
Data verification is the process of ensuring data accuracy, completeness, and consistency. It involves validating data against predefined standards, cross-checking sources, and detecting anomalies to maintain high-quality and reliable datasets for analytics and decision-making.

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