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Deep Learning in the Browser

Deep Learning in the Browser

We showcase examples of doing deep learning (DL) in the browser - for building explorable explanations to aid insight, for building model inference applications and even, for rapid prototyping and training ML model - using the emerging client-side Javascript libraries for DL.

Amit Kapoor

July 25, 2018
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  1. Historical Challenges ▸ Early JS libraries were too slow -

    CPU based ▸ Poor support for numerical operations ▸ Underdeveloped ecosystem for handling data and preprocessing, declarative visualisation, and reactive runtime
  2. Challenges with Rapid Prototyping ▸ Training on GPUs (integration with

    Node.js) ▸ Custom layers not supported ▸ Lack of feature parity with Python / C++ APIs