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Home / Glossary / Transfer Learning

What is Transfer Learning?

Transfer learning refers to a machine learning technique where a pre-trained model is adapted for a different but related task. It accelerates AI model training and improves performance with limited data.

Related Glossaries

  • Fairness (machine learning) Fairness in machine learning refers to the practice of designing AI models that make unbiased and equitable decisions across different demographic groups. It involves mitigating algorithmic bias, ensuring diverse training data, and implementing fairness-aware techniques to prevent discrimination in areas…
  • AI-Ready Data AI-Ready Data refers to data that is structured, validated, contextualized, and ready for immediate use in AI systems. It goes beyond stored or cleaned data by including the quality, lineage, access conditions, and business context required for reliable execution.
  • Data privacy Data privacy refers to the right of individuals to control how their personal information is collected, processed, and shared. It is regulated by laws like GDPR and CCPA, which mandate transparency, user consent, and security measures to protect sensitive data…
  • Public data transmission service Public data transmission service refers to networks and platforms that facilitate the secure exchange of publicly available data. These services enable governments, organizations, and researchers to access and share data while ensuring security, integrity, and interoperability.
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