Document worth reading: “Real numbers, data science and chaos: How to fit any dataset with a single parameter”

We current how any dataset of any modality (time-series, photos, sound…) could also be approximated by a well-behaved (regular, differentiable…) scalar function with a single real-valued parameter. Building upon elementary concepts from chaos precept, we undertake a pedagogical technique demonstrating how to alter this parameter in order to receive arbitrary precision fit to all samples of the data. Targeting an viewers of data scientists with a fashion for the curious and unusual, the outcomes launched proper right here develop on earlier associated observations regarding expressiveness vitality and generalization of machine learning fashions. Real numbers, data science and chaos: How to fit any dataset with a single parameter