Scientific Computing with Javascript

The primary objective of this session is to showcase Javascript as a viable language for mathematical and scientific computing. We’re going to explore some of the best libraries out there for symbolic math, statistics, set theory, as well as machine and deep learning, as well as talk about how tools like NaCl and d3.js, can be used for mathematical models that can run in the browser, and on the server.

 
1 favorite thumb_down thumb_up 0 comments visibility_off  Remove from Watchlist visibility  Add to Watchlist
 

Outline/structure of the Session

  1. We’ll first start off with an introduction to why many of the current languages used for math and science, have issues - non-asynchronous natures, server-based, and so on.
  2. We’re going to move on to some really good and extensive libraries, on symbolic computation, statistics, machine and deep learning and set theory. We’ll talk about the problems they’re typically meant for and used in, and we’ll check out some basic examples.
  3. We’re now going to go deeper into the rabbit hole, and discuss how one can run mathematical models and expose them over APIs using Node and Express; how these APIs can then be consumed using d3.js for visualizing results; running mathematical models inside Google’s Native Client, or on embedded hardware using Cylon.js; oh, and we might throw in some WebGL for fun!

Learning Outcome

The idea here is to leave participants with an appreciation of the scientific nature of Javascript, and introduce them to the viability of using the language for scientific computing.

Target Audience

Programmer, Computational Scientist, Frontend Engineer, Backend EngineerWe’ll first start off with an introduction to why many of the current languages used for math and science, have issues - non-asynchronous natures, server-based, and so on. We’re going

schedule Submitted 1 year ago

Comments Subscribe to Comments

comment Comment on this Proposal