AI Stories
Post Deployment Data Science with Wojtek Kuberski #56
Feb 13, 2025
Wojtek Kuberski, Co-Founder and CTO at NannyML, shares his expertise in AI and data science. He discusses the challenges of model monitoring post-deployment, including covariate shift and concept drift. Wojtek explains how NannyML's algorithms assess model performance without needing labels. He emphasizes the critical role of continuous monitoring to prevent silent failures that could impact businesses. The conversation also touches on his transition from freelancing to building a product-focused company in the ever-evolving data science landscape.
48:06
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Quick takeaways
- Freelancers can enhance their skills and adapt quickly by tackling challenging projects and seeking mentorship from experienced professionals.
- NannyML addresses the critical need for effective post-deployment model monitoring to counteract issues like data drift and concept drift.
Deep dives
Learning and Growth in Freelancing
Freelancers often lack senior guidance, which makes learning challenging. One effective way to grow is to seek mentorship from experienced professionals, while another approach is to tackle projects that are beyond one's current capabilities. Engaging with difficult tasks forces freelancers to adapt quickly by diving into research and real-world problem-solving, often leading them to develop valuable skills and insights on the job. For instance, individuals may need to self-educate on complex technical topics, such as machine learning, by studying literature and learning new coding practices while handling client projects.
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