Delivering a great buying experience makes all the difference in whether or not a user will convert to a customer. A core part of the eCommerce buying experience is creating an exceptional user journey from initial discovery to purchase. To learn more about accelerating the customer experience, we spoke to Nick Beighton, former CEO of ASOS, about his experience bringing a data-driven approach to online retail. 

Today, it is widely recognized that the most important ingredient for building a great machine learning model is training data. This practice of systematically building datasets to achieve better model performance is often referred to as data-centric AI. In the beginning however, most users don't have a lot of data on their own. So how can you get started? A good place to kick-off is typically a large public dataset. 

“This is the Unix philosophy: write programs that do one thing and do it well. Write programs to work together. Write programs that handle text streams, because that is a universal interface.”

Aerin is an engineering manager at Scale AI, leading a Catalog ML team. Below are Aerin's stories about what she does and why she loves working at Scale.

Aerin is an engineering manager at Scale AI, leading a Catalog ML team. Below are Aerin's stories about what she does and why she loves working at Scale.

As ML applications grow in size and complexity, testing is essential to ensure integrity and reliability of the application at hand. Given the non-deterministic nature of machine learning (ML) models, testing and continuous evaluation of ML systems is even more important.