Quality Assurance in Machine Learning: Enhancing Trust and Reliability

Explore the critical role of Quality Assurance (QA) in Machine Learning through this 28-minute conference talk by Serg Masis, Lead Data Scientist and bestselling author at Syngenta. Delve into the history of QA and its importance in AI/ML solutions, drawing lessons from other disciplines and industries. Discover how Explainable AI methods, MLOps best practices, data engineering, and data science contribute to quality control in machine learning. Examine the challenges of standardizing QA tasks in ML processes and the potential emergence of new roles in DevOps, SecOps, and MLOps teams. Gain insights into how data scientist and Machine Learning engineer roles may evolve to enhance quality, and learn practical steps for business stakeholders and practitioners to increase the trustworthiness of AI/ML technology for end-users.

QA in ML