Deep Learning Frameworks

Deep Learning is a subset of Machine Learning which deals with deep neural networks. It is based on a set of algorithms that attempt to model high-level abstractions in data by using multiple processing layers, with complex structures or otherwise, composed of multiple non-linear transformations. Deep Learning is able to solve more complex problems and perform greater tasks. Deep Learning Framework is an essential supporting fundamental structure that helps to make complexity of DL little bit easier. There are top 10 deep learning frameworks:

 

  • Tensorflow
  • Theano
  • Keras
  • Caffe
  • Torch
  • Deeplearning4j
  • MXNet
  • Microsoft Cognitive Toolkit
  • Lasagne
  • BIgDL

Related Conference of Deep Learning Frameworks

Jan 30-31, 2019

World Congress on Wireless Technology

Osaka , Japan
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6th Global Meet on Wireless, Aerospace & Satellite Communications

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May 17-18, 2019

10th World Congress on Biosensors and Bioelectronics

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3rd World Congress on Wind & Renewable Energy

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3rd World Congress on Wind & Renewable Energy

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Building Materials & Construction Technologies

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6th International Conference on Steel and Concrete Structures

July 29-30, 2019 | Mercure albert park | Melbourne, Australia
September 18-19, 2019

8th International Conference on Biostatistics & Bioinformatics

San Francisco, USA
September 18-19, 2019

8th International Conference on Big Data Analytics & Data Mining

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6th International Conference and Expo on Computer Graphics & Animation

Toronto | Ontario | Canada
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6th World Machine Learning and Deep Learning Congress

Helsinki, Finland
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12th International Conference & Exhibition on Biosensors & Bioelectronics

Vancouver | British Columbia | Canada
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