Karin Schöfegger is a seasoned ML product manager who knows how to create successful AI/ML products and mitigate the risks involved. In this episode, she shares her insights about challenges in building AI products. Tune in to learn about:
- How to align the business side and the data science side of product development
- What's the difference between traditional software development and machine learning development
- How to bring customer understanding into data science and engineering
- What are the most common traps in data science
- Why it's essential to work with realistic data instead of picture-perfect datasets
- How to get buy-in from stakeholders for ethical AI
Data Democratization Podcast: Stories about AI, Data, and Privacy