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Salem Ameen
Worked at University of Salford
Attends University of Salford
Lives in Manchester
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Salem Ameen

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Direct Graphical Models library v1.4.0 has been just released with lots of improvements and bug fixes since v1.3.1, including improved performance, simplified user interface and much of new functionality, like:
 - new feature extraction module,
 - new advanced pairwise potentials,
 - extended visualization engine, and
 - evaluation of the classification results, etc.
DGM is a C++ library implementing various tasks in probabilistic graphical models with pairwise dependencies. The library aims to be used for the Markov and Conditional Random Fields (MRF / CRF), Markov Chains, Bayesian Networks, etc.
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Salem Ameen

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I would like to ask if there is a summer school for deep learning or machine learning in general that is available this month and is still open for registration? Please if know.
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Great, thanks for sharing.

Salem Ameen

Unsupervised Learning  - 
 
I would like to know please if PCA can resize or reduce the size of the image for example I have image of size 200x200 pixels, can PCA  reduces it to 100x100 pixels. By the way I know I can resizing using Matlap or other software and the job of PCA is dimensionality reduction.
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Valentin Fedulov's profile photoSalem Ameen's profile photoJiatong Li's profile photoGeppetto Null's profile photo
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+Jiatong Li, what have to be human understandable after PCA, are the projected images, which makes perfect sense after all, as they are just "approximations" of the original ones after preserving a certain fraction of the total variance.
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Machine Learning  - 
 
I would like to know please if PCA can resize or reduce the size of the image for example I have image of size 200x200 pixels, can PCA  reduces it to 100x100 pixels. By the way I know I can resizing using Matlap or other software and the job of PCA is dimensionality reduction.
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We just posted a new release of our MIT Press Deep Learning book draft, with the first two parts (out of three) of the book basically completed and sent to reviewers. Feedback will continue to improve these two parts, I'm sure, thanks to all those who gave us feedback and to all those who will in the future. Enjoy!
http://www.iro.umontreal.ca/~bengioy/dlbook/
Deep Learning. An MIT Press book in preparation. Yoshua Bengio, Ian Goodfellow and Aaron Courville. Citing the book in preparation. To cite this book in preparation, please use the following bibtex entry: @unpublished{Bengio-et-al-2015-Book, title={Deep Learning}, author={Yoshua Bengio and Ian ...
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This is my first trying with RNN
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Work
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  • University of Salford
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  • deep learning
  • Machine Learning Department
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