Deep Learning in Clojure with Cortex

Deep Learning in Clojure With Cortex

  • The training data consists of 25,000 images of cats and dogs.
  • It reads in the external nippy file that contains the trained network description, takes a random image from the testing directory, and classifies it.
  • We want all the dog images to be under a “dog” directory and the cat images under the “cat” directory so that the all the indexed images under them have the correct “label”.
  • How many times it thought a cat was really a cat and how many times it got it wrong.
  • We need all the images to be the same size as well as in a directory structure that is split up into the training and test images.

There is an awesome new Clojure-first machine learning library called Cortex that was open sourced recently. I’ve been exploring it lately and …
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GitHub

Nice #GitHub project: Deep Q-learning for Super #Mario Bros. #DeepLearning #MachineLearning

  • Please note that GitHub no longer supports old versions of Internet Explorer.
  • A modification of Google’s Deep Q-Network to learn to play Super Mario Bros.
  • For instructions and a summary of changes to the original Google project, please see this blog post.
  • We recommend upgrading to the latest Internet Explorer , Google Chrome , or Firefox .
  • It uses a double deep Q network to control an open-source Nintendo Entertainment System emulator called FCEUX.

Read the full article, click here.


@randal_olson: “Nice #GitHub project: Deep Q-learning for Super #Mario Bros. #DeepLearning #MachineLearning”


DeepQNetwork – A modification of Google’s Deep Q-Network to learn to play Super Mario Bros.


GitHub