The first article in this series about deep neural network basics offers a unique perspective on the development and application of machine learning (ML) by comparing classic computational methods with modern ML approaches. Using the example of calculating a sine function – a basic trigonometric function – we highlight the difference between the conventional way of solving problems in the classic software approach and how to implement the calculation with deep neural networks. We’ll also implement the example in Kotlin, and in doing so, we’ll consider Kotlin-specific topics.