About“It always seems impossible until it is done.” - Nelson Mandela
Brooke Wenig is the Machine Learning Practice lead at Databricks. She consults and implements various Machine Learning pipelines for Databricks' customers, such as: product recommendation systems, big data architecture design, etc. She developed and delivered Data Science and Machine Learning courses at all three Spark Summits in 2017 (Boston, SF, and Dublin), as well as private trainings to dozens of clients.
Prior to joining Databricks, she was a teaching associate at UCLA, where she taught graduate machine learning, senior software engineering, and introductory programming courses. Previously, Brooke worked at Splunk and Under Armour as a KPCB fellow. She holds an MS in computer science from UCLA with a focus on distributed machine learning. Brooke speaks Mandarin Chinese fluently and is advanced in Spanish.
When she's not nerding out, she enjoys riding her bike, travelling, and trying new cuisines.