What are the best practices for data cleaning in AI governance?
Data cleaning is an essential step in any machine learning project, as it can affect the quality, performance, and reliability of the models. However, data cleaning is not only a technical task, but also a ethical and legal one, especially when it comes to AI governance. AI governance is the process of ensuring that AI systems are aligned with the values, principles, and regulations of the stakeholders and society. In this article, you will learn what are the best practices for data cleaning in AI governance, and how they can help you avoid common pitfalls and risks.
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Michael Shost, PMI PMP, ACP, RMP, CEH, SPOC, SA, PMO-FO?? Visionary PMO Leader & AI/ML/DL Innovator | ?? Certified Cybersecurity Expert & Strategic Engineer | ???…
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Vaibhav PandeyBuilding ad tech platform for growth | Co-founder & CTO, Tyroo
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MSP RajaLead AI/ML Scientist | Machine Learning Researcher | AI in Mental Health | Generative AI | Prompt Engineering | AI in…