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JavaScript and number crunching may seem an odd pair, but this is rapidly changing. In this talk, Athan will discuss the current state-of-the-art for numeric computation and machine learning in JavaScript. He will introduce libraries for statistical computing, neural networks, and multidimensional data structures and highlight emerging technologies such as WebAssembly and Node.js native add-ons. Next, he will discuss what to look for in numeric computing libraries, common implementation mistakes, and how to avoid portability issues. By the end of this talk, you will understand why JavaScript is poised to become the next big thing for data science and numeric computing. To conclude, he will outline future steps and identify opportunities for community development of next-generation tools.
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Math, Machine Learning, and JavaScript - Intermediate
Athan Reines
Athan Reines is a full-stack engineer and data scientist. He has a PhD in Physics, where he used machine learning and time series analytics to probe biological systems at the nanoscale. He currently works full-time on open source projects to facilitate numerical computing in Node.js and JavaScript.