Machine Learning Security

Machine Learning Security refers to the practices and technologies designed to protect machine learning systems from vulnerabilities and attacks. This encompasses safeguarding data integrity, model robustness, and privacy while preventing adversarial attacks that can manipulate AI outcomes. As organizations increasingly rely on machine learning for critical applications, ensuring security against threats such as data poisoning, model inversion, and adversarial examples is essential. Implementing effective machine learning security measures enhances trust in AI solutions and mitigates risks, enabling businesses to leverage machine learning technologies confidently and responsibly.

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