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Autograd download for Windows

Free download Autograd Windows app to run online win Wine in Ubuntu online, Fedora online or Debian online

This is the Windows app named Autograd whose latest release can be downloaded as 1.0.zip. It can be run online in the free hosting provider OnWorks for workstations.

Download and run online this app named Autograd with OnWorks for free.

Follow these instructions in order to run this app:

- 1. Downloaded this application in your PC.

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- 3. Upload this application in such filemanager.

- 4. Start any OS OnWorks online emulator from this website, but better Windows online emulator.

- 5. From the OnWorks Windows OS you have just started, goto our file manager https://www.onworks.net/myfiles.php?username=XXXXX with the username that you want.

- 6. Download the application and install it.

- 7. Download Wine from your Linux distributions software repositories. Once installed, you can then double-click the app to run them with Wine. You can also try PlayOnLinux, a fancy interface over Wine that will help you install popular Windows programs and games.

Wine is a way to run Windows software on Linux, but with no Windows required. Wine is an open-source Windows compatibility layer that can run Windows programs directly on any Linux desktop. Essentially, Wine is trying to re-implement enough of Windows from scratch so that it can run all those Windows applications without actually needing Windows.

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Autograd


DESCRIPTION

Autograd can automatically differentiate native Python and Numpy code. It can handle a large subset of Python's features, including loops, ifs, recursion and closures, and it can even take derivatives of derivatives of derivatives. It supports reverse-mode differentiation (a.k.a. backpropagation), which means it can efficiently take gradients of scalar-valued functions with respect to array-valued arguments, as well as forward-mode differentiation, and the two can be composed arbitrarily. The main intended application of Autograd is gradient-based optimization. For more information, check out the tutorial and the examples directory. We can continue to differentiate as many times as we like, and use numpy's vectorization of scalar-valued functions across many different input values.



Features

  • Simple neural net
  • Convolutional neural net
  • Recurrent neural net
  • LSTM
  • Neural Turing Machine
  • Backpropagating through a fluid simulation


Programming Language

Python



This is an application that can also be fetched from https://sourceforge.net/projects/autograd.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.


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