This is the Linux app named DIGITS whose latest release can be downloaded as Updatetov6.1.1.zip. It can be run online in the free hosting provider OnWorks for workstations.
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The NVIDIA Deep Learning GPU Training System (DIGITS) puts the power of deep learning into the hands of engineers and data scientists. DIGITS can be used to rapidly train the highly accurate deep neural network (DNNs) for image classification, segmentation and object detection tasks. DIGITS simplifies common deep learning tasks such as managing data, designing and training neural networks on multi-GPU systems, monitoring performance in real-time with advanced visualizations, and selecting the best performing model from the results browser for deployment. DIGITS is completely interactive so that data scientists can focus on designing and training networks rather than programming and debugging. DIGITS is available as a free download to the members of the NVIDIA Developer Program. DIGITS is available on NVIDIA GPU Cloud (NGC) as an optimized container for on-demand usage. Sign-up for an NGC account and get started with DIGITS in minutes.
- Interactively train models using TensorFlow and visualize model architecture using TensorBoard
- Integrate custom plug-ins for importing special data formats such as DICOM used in medical imaging
- Pre-trained UNET model added to the DIGITS model store for image segmentation of medical images
- Design, train and visualize deep neural networks for image classification, segmentation and object detection using Caffe, Torch and TensorFlow
- Download pre-trained models such as AlexNet, GoogLeNet, LeNet and UNET from the DIGITS Model Store
- Perform hyperparameter sweep of learning rate and batch size for improved model accuracy
- Schedule, monitor, and manage neural network training jobs, and analyze accuracy and loss in real time
- Import a wide variety of image formats and sources with DIGITS plug-in
- Scale training jobs across multiple GPUs automatically
This is an application that can also be fetched from https://sourceforge.net/projects/digits.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.