A Guide to Implementing MLOps: From Data to Operations
暫譯: MLOps 實施指南：從數據到運營

Prafful Mishra is a seasoned engineer with extensive experience in operationalizing machine learning across organizations of varying scales. His expertise includes Site Reliability & Platform Engineering, and artificial intelligence, with a particular focus on MLOps. Prafful is passionate about emerging technologies such as quantum computing, federated learning, and explainable AI. He actively shares his insights through writing and speaking engagements, aiming to demystify complex concepts and foster innovation in the tech community. A strong advocate for open-source contributions, Prafful supports the democratization of technology, believing that collaborative development leads to more accessible and robust solutions.

Prafful Mishra 是一位經驗豐富的工程師，擁有在不同規模的組織中實現機器學習的廣泛經驗。他的專業領域包括網站可靠性與平台工程，以及人工智慧，特別專注於 MLOps。Prafful 對於量子計算、聯邦學習和可解釋的人工智慧等新興技術充滿熱情。他透過寫作和演講活動積極分享自己的見解，旨在揭開複雜概念的神秘面紗，並促進科技社群的創新。作為開源貢獻的強烈倡導者，Prafful 支持技術的民主化，堅信協作開發能夠帶來更具可及性和穩健性的解決方案。