Rachel Thomas

Biography

Rachel Thomas is a professor at the University of San Francisco Data Instituteand co-founder of fast.ai, which created the “Practical Deep Learning for Coders”course that over 200,000 students have taken and which has been featured in The Economist, MIT Tech Review, and Forbes. She was selected by Forbes as one of 20 Incredible Women in AI, earned her math PhD at Duke, and was an early engineer at Uber. Rachel is a popular writer and keynote speaker. In her TEDx talk, she shares what scares her about AI and why we need people from all backgrounds involved with AI.

Rachel’s writing has been read by nearly a million people; has been translated into Chinese, Spanish, Korean, & Portuguese; and has made the front page of Hacker News 9x. Some of her most popular articles include:

• If you think women in tech is just a pipeline issue, you haven’t been paying attention
• How to change careers and become a data scientist- one quant’s experience
• The real reason women quit tech, and how to address it
• Google’s AutoML: Cutting Through the Hype
• An Introduction to Deep Learning for Tabular Data

Rachel’s talks include:

• The Barriers to AI are Lower than You Think (MIT Technology Review conference)
• How to Learn Deep Learning (when you’re not a computer science PhD) (SF Machine Learning Meetup)
• Using randomness to make code much faster (featured talk at PyBay)
• How the Jupyter Notebook helped fast.ai teach deep learning to 50,000 students (keynote at JupyterCon)
• Analyzing & Preventing Unconscious Bias in Machine Learning (keynote at QCon.ai)
• Some Healthy Principles About Ethics & Bias In AI (keynote at PyBay)