Analyzing & Preventing Unconscious Bias in Machine Learning

I just briefly wanted to say a little bit about my background. I studied Math and Computer Science in college and then did a Ph.D. in Math. I worked as a quant in Energy Trading and that's where I first started working with data. I was an early data scientist and backend developer at Uber. I taught full stack software development at Hackbright. I really love teaching and I think I'll always return to teaching in some form. And then two years ago, together with Jeremy Howard, I started fast.ai with the goal of making deep learning more accessible and easier to use. I'm on Twitter @math_rachel and, as William said, I blog about diversity on Medium @racheltho, and I blog about data science at fast.ai. I just have one slide about fast.ai. We have this, as William mentioned, a totally free course, "Practical Deep Learning for Coders." The only prerequisite is one year of coding experience. It's distinctive in that there are no advanced math prerequisites, yet it takes you to the state-of-the-art. We've had a lot of success. We've had students get jobs at Google Brain, have their work featured on HBO and in Forbes, launch new companies, get new jobs.