Deep Learning Frameworks

New #cuDNN 5.1, 2.7x faster training of #deeplearning networks with 3x3 convolutions.

  • Deep learning course: Getting Started with the Caffe Framework
  • Choose a deep learning framework from the list below, download the supported version of cuDNN and follow the instructions on the framework page to get started.
  • Chainer is a deep learning framework that’s designed on the principle of define-by-run.
  • Caffe is a deep learning framework made with expression, speed, and modularity in mind.

Read the full article, click here.


@GPUComputing: “New #cuDNN 5.1, 2.7x faster training of #deeplearning networks with 3×3 convolutions.”


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. Choose a deep learning framework from the list below, download the supported version of cuDNN and follow the instructions on the framework page to get started.


Deep Learning Frameworks

Microsoft improves programming flexibility of its AI toolkit

Microsoft improves programming flexibility of its #AI toolkit

  • Microsoft improves programming flexibility of its AI toolkit
  • Earlier this year, Microsoft made its open source Computational Network Toolkit (CNTK), a tool used to speed up advances in artificial intelligence, available on GitHub .
  • We will continue working with the community to help advance CNTK, including the addition of more popular programming languages like Python.
  • CNTK 1.5 includes a revamped I/O architecture, including more flexible readers for text and speech, making it easier to input popular formats into the toolkit for deep learning training.
  • Today, with CNTK 1.5, we are adding significant language enhancements, an expanded toolbox of features, and improved readers for text and speech.

Read the full article, click here.


@MSFTnews: “Microsoft improves programming flexibility of its #AI toolkit”


The Microsoft Research blog shares stories of collaborations with computer scientists at academic and scientific institutions to advance technical innovations in computing, as well as related events, scholarships, and fellowships.


Microsoft improves programming flexibility of its AI toolkit