MILJS : Brand New JavaScript Libraries for Matrix Calculation and Machine Learning
This provides efficient, browser-based tools for developers and researchers working on machine learning in JavaScript, though it is incremental as it builds on existing concepts.
The authors introduced MILJS, a collection of JavaScript libraries for matrix calculation and machine learning, with their core matrix library Sushi achieving 177 times faster matrix multiplication than the fastest JavaScript benchmark.
MILJS is a collection of state-of-the-art, platform-independent, scalable, fast JavaScript libraries for matrix calculation and machine learning. Our core library offering a matrix calculation is called Sushi, which exhibits far better performance than any other leading machine learning libraries written in JavaScript. Especially, our matrix multiplication is 177 times faster than the fastest JavaScript benchmark. Based on Sushi, a machine learning library called Tempura is provided, which supports various algorithms widely used in machine learning research. We also provide Soba as a visualization library. The implementations of our libraries are clearly written, properly documented and thus can are easy to get started with, as long as there is a web browser. These libraries are available from http://mil-tokyo.github.io/ under the MIT license.