Gradient Descent

We sit down with Erik to discuss gradient descents and how understanding this can lead to demystifying machine learning. We talk about the value of knowing how things work under the covers, as well as maths, functional programming, and many other topics, including why he chose Kotlin, and what he likes and dislikes of the language

About Erik Meijer

Erik Meijer has been trying to bridge the ridge between theory and practice for most of his career. He is perhaps best known for his work on, amongst others, the Haskell, C#, Visual Basic, and Dart programming languages, as well as for his contributions to LINQ and the Reactive Framework (Rx). Most recently he is on a quest to make uncertainty a first-class citizen in mainstream programming languages

Show Notes

Additional notes

Kotlin and Google Cloud Platform

We sit down with James Ward from Google to discuss everything Google Cloud Platform and Kotlin. And as a bonus dive into the past, and Kubernetes Continue reading

Maths and Kotlin

Published on September 30, 2020

Fritz2

Published on September 14, 2020