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

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Compose for Desktop

We sit down to talk to Nikolay Igotti, who's now leading the efforts of Compose for Desktop at JetBrains. We talk about why the need for a new UI framework for Desktop, how Compose for Desktop works, and what's planned for the future. Continue reading

Kotlin in Space

Published on December 14, 2020

GraphQL with Apollo and Kotlin

Published on November 26, 2020