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.

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@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

Keras: Deep Learning library for Theano and TensorFlow

Keras:Deep Learning library for Theano & TensorFlow Tutorial   #DataScience #MachineLearning

  • The core data structure of Keras is a model , a way to organize layers.
  • By default, Keras will use Theano as its tensor manipulation library.
  • The main type of model is the Sequential model, a linear stack of layers.
  • To be able to easily create new modules allows for total expressiveness, making Keras suitable for advanced research.
  • Getting started: 30 seconds to Keras

Read the full article, click here.


@gcosma1: “Keras:Deep Learning library for Theano & TensorFlow Tutorial #DataScience #MachineLearning”


Keras is a minimalist, highly modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano. It was developed with a focus on enabling fast experimentation. Being able to go from idea to result with the least possible delay is key to doing good research.


Keras: Deep Learning library for Theano and TensorFlow