Big trends on how Companies are identifying the right data to train AI & ML | VB Transform 2020
The right data: Big trends on how Companies are identifying the right data to train AI & ML algorithms accurately to tackle various issues such as customer service, personalization, risk & fraud with increased speed and agility
As AI & ML gains prominence and becomes an integral part of businesses across industries, there is a need to ensure that the algorithms are accurate, explainable, and trustworthy to be able to solve business problems effectively, provide great ROI and ensure customer satisfaction. To do this, AI teams not only need to select the right AI models, but also need to train them on the right datasets and make sure they address issues such as over fitment of data, identifying and correcting cyclical trends in the data, ensuring the data is labeled accurately etc. Join our panel of industry stalwarts who will discuss and debate this.
Jaime Delange, Director of Product, Slack
Hui Wang, VP of Data Science, PayPal
Dimitris Tsementsiz, Senior Quantitative Researcher, Goldman Sachs
Jacob Wilson, Principal, PwC
Moderated by Jed Dougherty, VP of Field Engineering, Dataiku