Training Conversational Agents on Noisy Data
This session will address both sides of the challenge: (1) using data-efficient strategies during the utterance collection and annotation phases to optimize the trade-off between cost and quality when collecting training data, (2) using data-driven approaches to train and generate behaviors for a conversational agent despite noisy data and lack of training labels.
Databricks is the data and AI company. Thousands of organizations worldwide rely on Databricks’ open and unified platform for data engineering, machine learning and analytics. Founded by the original creators of Apache Spark™, Delta Lake and MLflow, Databricks is on a mission to solve the world’s toughest problems.
DataRobot is the leader in enterprise AI, delivering trusted AI technology and ROI enablement services to global enterprises. DataRobot’s enterprise AI platform democratizes data science with end-to-end automation for building, deploying, and managing machine learning models.