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ConvNetJS might be a bit more popular than NVIDIA DIGITS. We know about 2 links to it since March 2021 and only 2 links to NVIDIA DIGITS. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
I'm not quite sure if this is the place to ask it, but I'll give it a shot. Several years ago, during my PhD, I used to train small CNNs using NVIDIA DIGITS tool (https://developer.nvidia.com/digits), that is basically a frontend to tasks such as build datasets, configure training parameters, follow real time training data (epochs), test classification and export training for usage. This is a oversimplified... Source: over 1 year ago
Also frameworks which make moving to multiGPU easy, like DIGITS: https://developer.nvidia.com/digits. Source: almost 3 years ago
One, Two, Three, and so on. ANYone does use JS for machine learning. Though that's unconventional, python is by far the leading language for ML. Maybe you meant to say "EVERYone"? Source: about 1 year ago
Another good one is ConvNetJS - but I don’t have much experience using that. - Source: dev.to / almost 3 years ago
Knet - Knet is a deep learning framework that supports GPU operation and automatic differentiation using dynamic computational graphs for models.
Keras - Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.
PyTorch - Open source deep learning platform that provides a seamless path from research prototyping to...
Microsoft Cognitive Toolkit (Formerly CNTK) - Machine Learning
Floyd - Heroku for deep learning
TFlearn - TFlearn is a modular and transparent deep learning library built on top of Tensorflow.