For many years, the programming language of choice for machine learning was one of the following: Python, R, MATLAB, C++. This is not due to some specific language features, but because of the infrastructure around it: libraries and tools. Swift is a relatively young programming language, and anyone who chooses it as a primary tool for machine learning development should start from the very basic building blocks, and build his own tools and libraries. Recently, Apple became more open to third-party Python machine learning tools: Core ML can work with some of them.
Here is a list of components that are needed for the successful machine learning research and development, and examples of popular libraries and tools of the type:
- Linear algebra: Machine learning developer needs data structures like vectors, matrices, and tensors with compact syntax and hardware...
