Speaker:Feifei Wang

Title: Databricks Demo - Transfer Learning with MLflow, the #1 Tool to Learn Today

Speaker: Feifei Wang

Abstract: Feifei will be doing a live demo for solving an image classification problem (cats vs dogs) using the transfer learning TensorFlow package together with MLflow for logging and model registry on Databricks. Databricks is an industry-leading, cloud-based data analytics/science/engineering platform used for processing and transforming massive quantities of data and exploring the data through machine learning models. It is founded by the creators of Apache Spark. They are also the creators of MLflow (an open-source platform for managing the end-to-end machine learning lifecycle). If you are interested in reviewing concepts from CNN deep learning, understanding how transfer learning algorithms work, learning more about MLOps in general, or just stopping by and grabbing some Databricks swag, please feel free to join us.

About the speaker: Dr. Feifei Wang is currently a senior data scientist at the machine learning practice team at Databricks. Her team is highly specialized in customer-facing data science work at Databricks. They deliver professional services engagements to help their customers build, scale, and optimize ML pipelines, as well as teach courses on distributed ML & deep learning. They work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations, as well as support internal subject matter expert teams.

Before joining Databricks this year, she recently spent 5 years at Disney where she was a senior decision scientist. At Disney, Feifei supported the Walt Disney Studios projects, built machine learning models, and customized forecasting and optimization tools to support internal clients, such as marketing and distribution teams for their business decision-making.

Prior to joining Disney, she was doing research in Robotics at Iowa State University under Dr. Yan-Bin Jia (CS) and Dr. Scott Hansen (Math). She received her Ph.D. co-major in Applied Mathematics and Computer Science from Iowa State University in 2017.