Deep learning algorithms use large amounts of data and the computational power of the GPU to learn information directly from data such as images, signals, and text. NVIDIA® DIGITS offers an interactive workflow-based solution for image classification. Deep learning frameworks offer more flexibility with designing and training custom deep neural networks and provide interfaces to common programming language. The NVIDIA Deep Learning SDK offers powerful tools and libraries for the development of deep learning frameworks such as Caffe, CNTK, TensorFlow, Theano, and Torch.
The NVIDIA Deep Learning SDK provides powerful tools and libraries for designing and deploying GPU-accelerated deep learning applications. It includes libraries for deep learning primitives, linear algebra, sparse matrices, multi-GPU communications, and the complete CUDA C\C++ development environment.
NVIDIA DIGITS helps computer vision data scientists and engineers solve complex image classification problems. DIGITS lets you quickly design the best deep neural network (DNN) for your data—interactively, without writing any code—to reach state-of-the-art results with deep learning.

Import data for image classification and object detection neural networks

Choose predefined LeNet, AlexNet, GoogLeNet or provide custom networks

Visualize deep neural network architectures

Import data for image classification and object detection neural networks

Choose predefined LeNet, AlexNet, GoogLeNet or provide custom networks

Visualization of inference results
The NVIDIA Deep Learning SDK accelerates widely used deep learning frameworks such as Caffe, CNTK, TensorFlow, Theano, and Torch, as well as many other deep learning applications. Visit the Deep Learning Frameworks page to learn more about these popular deep learning frameworks, their key features, and how to download and get started.