Recording brought to you by American Express. https://americanexpress.io/kotlin-jobs Differentiation tells us how to make a small change to the inputs of a function, so as to produce the largest change in output. At first, this idea may not seem very important for software engineers, but differential equations can be found at the heart of every other engineering discipline and nearly every major contribution to the physical sciences in the last three centuries. As digital computers begin to interface with the physical world, derivatives will begin to play an increasingly significant role in computing. Contrary to popular belief, #derivatives are surprisingly simple to understand and compute. In this talk, we will see how to implement automatic differentiation in Kotlin, using functional programming, and see some applications for physical simulation, machine learning and automatic testing. No prior experience or mathematical background is assumed or required. Resources: KotlinConf website: https://jb.gg/fyaze5 KotlinConf on Twitter: https://twitter.com/kotlinconf Kotlin website: https://jb.gg/pxrsn6 Kotlin blog: https://jb.gg/7uc7ow Kotlin on Twitter: https://twitter.com/kotlin #KotlinConf19 #Kotlin #JetBrains About the Presenter: Ph.D. Student in Machine Learning at Mila.