Personalization from a Product Perspective

3 key takeaways:
• Product development cycle for ML-driven products, and how it’s similar and different to typical software product development
• 0 to 1: Building the first machine learning model in a product. What problems is machine learning good for? What should you do first? How do you get organizational buy-in?
• 1 to n: How to improve on existing machine learning models and iterate fast
• My talk will illustrate the above through examples of building ML products across companies at different stages, from early stage startups, high-growth mid-size, to large tech companies like Spotify