Code it

Python is not the only option for programming machine learning applications. There’s a growing community of developers who are using JavaScript to run machine learning models.

While JavaScript is not a replacement for the rich Python machine learning landscape (yet), there are several good reasons to have JavaScript machine learning skills. Here are four.

Private machine learning

Fast and customized ML models

Easy integration of machine learning in web and mobile applications

Server side JavaScript machine learning is maturing

JavaScript for programming machine learning offers several advantages over Python and R, namely privacy, speed, and staying on the device.

read more at https://venturebeat.com/2021/04/23/4-reasons-to-learn-machine-learning-with-javascript/

Simple phenomena, such as how sap flows down a tree trunk, are straightforward and can be captured in a few lines of code using what mathematicians call linear differential equations.

But in nonlinear systems, interactions can affect themselves: When air streams past a jet’s wings, the air flow alters molecular interactions, which alter the air flow, and so on. This feedback loop breeds chaos, where small changes in initial conditions lead to wildly different behavior later, making predictions nearly impossible — no matter how powerful the computer.

“This is part of why it’s difficult to predict the weather or understand complicated fluid flow,” said Andrew Childs, a quantum information researcher at the University of Maryland. “There are hard computational problems that you could solve, if you could [figure out] these nonlinear dynamics.”

That may soon be possible. In separate studies posted in November, two teams — one led by Childs, the other based at the Massachusetts Institute of Technology — described powerful tools that would allow quantum computers to better model nonlinear dynamics.