Welcome to Vidora’s Video Blog Series! Every two weeks, we will take an in-depth look at a different topic in the ML universe. We break down the key challenges businesses face with ML today, why they should matter to you, and what solutions will help you make the most of the technology. In this post, we look at techniques for making machine learning easy.
For part two of Vidora’s video blog series, Vidora Engineer Neven Wang-Tomic interviews Vidora Co-Founder and Head of Product Philip West about how to make complex ML technology accessible and understandable for anyone in any organization. They firstly discuss the concept of the “black box” in machine learning. Next, they talk about why it’s important to dig further into the predictions that a ML system makes. Finally, they talk about what methods provide more transparency in the machine learning process.
Host: Neven Wang-Tomic, Guest: Philip West
Vidora enables anyone in any business to build and use complex ML models. With Vidora’s self-service platform, Cortex, ML is intuitive, interpretable and fast. Cortex also automates the entire machine learning pipeline from raw data to model outputs. Experts in ML and artificial intelligence from Stanford, Berkeley and Caltech developed Cortex. Finally, Cortex sits at the heart of some of the largest global brands, such as Walmart, News Corp, and Discovery.