Based on our record, Keras seems to be a lot more popular than NVIDIA DIGITS. While we know about 32 links to Keras, we've tracked only 2 mentions of 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
The core model architecture for Magika was implemented using Keras, a popular open source deep learning framework that enables Google researchers to experiment quickly with new models. - Source: dev.to / 17 days ago
As a beginner, I was looking for something simple and flexible for developing deep learning models and that is when I found Keras. Many AI/ML professionals appreciate Keras for its simplicity and efficiency in prototyping and developing deep learning models, making it a preferred choice, especially for beginners and for projects requiring rapid development. - Source: dev.to / 2 months ago
After setting the variables for the environment, the next step is to install dependencies. To use Gemma, KerasNLP is the dependency used. KerasNLP is a collection of natural language processing (NLP) models implemented in Keras and runnable on JAX, PyTorch, and TensorFlow. - Source: dev.to / 2 months ago
Other popular machine learning tools include PyTorch, Keras, and Scikit-learn. PyTorch is an open-source machine learning library developed by Facebook that is known for its ease of use and flexibility. Keras is a high-level neural networks API that is written in Python and is known for its simplicity. Scikit-learn is a machine learning library for Python that is used for data analysis and data mining tasks. - Source: dev.to / about 1 year ago
I'm not aware of anything off-the-shelf, but if you have sufficient programming experience, one way to do this would be to build a large dataset of reference images and pictures and use something like keras to train a convolutional neural network on them. Source: about 1 year ago
Knet - Knet is a deep learning framework that supports GPU operation and automatic differentiation using dynamic computational graphs for models.
TensorFlow - TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.
PyTorch - Open source deep learning platform that provides a seamless path from research prototyping to...
Floyd - Heroku for deep learning
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
ConvNetJS - ConvNetJS is a Javascript library for training Deep Learning models (Neural Networks) entirely in a browser.