#126 Make Your A/B Testing More Effective and...

The role of the machine learning engineer is being rewritten in real time. AI coding assistants are absorbing parts of the day-to-day, planning and evaluation are eating up more of the week, and the lines between machine learning engineer, AI engineer, and data scientist are blur ...  Show more

Every conversation about AI in data eventually arrives at the same question: which roles survive, and which ones get automated away? Generative AI can already draft SQL, build dashboards, and run exploratory analysis — but it still can't sit with a business stakeholder and untang ...  Show more

Just about anything can be A/B tested, and it can be done by just about anyone. Nicole Lau, Product Manager at eBay, is here with us to expla ...

Stefan Thomke, professor at Harvard Business School, says running experiments can give companies tremendous value, but too often business leaders make decisions based on intuition. While A/B testing on large transaction volumes is common practice at Google, Booking.com, and Netfl ...  Show more

Conjoint analysis is like AB tester, but more bigger more better: instead of testing one or two things, you can test potentially dozens of options. Where might you use something like this? Well, if you wanted to design an entire hotel chain completely from scratch, and to do it i ...  Show more

Let’s talk about production and winning cases. It’s not only about acquiring new clients, but also acquiring new clients that can deliver results. A potential breakthrough using Artificial Intelligence, AI. How do we frame, understand, and implement the best of AI’s capabilities? ...  Show more