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A few weeks ago I introduced bat-country, my implementation of a lightweight, extendible, easy to use Python package for deep dreaming and inceptionism. The reception of the library was very good, so I decided that it would be interesting to…
Read More of Deep dream: Visualizing every layer of GoogLeNet
One of the main benefits of the bat-country Python package for deep dreaming and visualization is its ease of use, extensibility, and customization. And let me tell you, that customization really came in handy last Friday when the Google Research…
Read More of Generating art with guided deep dreaming.
We can’t stop here, this is bat country. Just a few days ago, the Google Research blog published a post demonstrating a unique, interesting, and perhaps even disturbing method to visualize what’s going inside the layers of a Convolutional Neural…
Read More of bat-country: an extendible, lightweight Python package for deep dreaming with Caffe and Convolutional Neural Networks
Last week I wrote a post detailing my experience with CUDAMat, Deep Belief Networks, and Python using my MacBook Pro. The post is fairly long and full of screenshots to document my experience. But the gist of it is this:…
Read More of Deep Learning on Amazon EC2 GPU with Python and nolearn
Grab the tissues. This is a tail of my MacBook Pro, a GPU, and the CUDAMat library — and it doesn’t have a happy ending. Two weeks ago I posted a Geting Started with Deep Learning and Python guide. The…
Read More of My Experience with CUDAMat, Deep Belief Networks, and Python
Update – January 27, 2015: Based on the feedback from commenters, I have updated the source code in the download to include the original MNIST dataset! No external downloads required! Update – March 2015, 2015: The nolearn package has now…
Read More of Getting Started with Deep Learning and Python
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