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Machine Learning - complete course notes Home Stanford Machine Learning The following notes represent a complete, stand alone interpretation of Stanford's machine learning course presented by Professor Andrew Ng and originally posted on the ml-class.org website during the fall 2011 semester. The topics covered are shown below, although for a more detailed summary see lecture 19. The only content not covered here is the Octave/MATLAB programming. »

Setting up a Deep Learning Machine from Scratch (Software) A detailed guide to setting up your machine for deep learning research. Includes instructions to install drivers, tools and various deep learning frameworks. This was tested on a 64 bit machine with Nvidia Titan X, running Ubuntu 14.04 There are several great guides with a similar goal. Some are limited in scope, while others are not up to date. This guide is based on (with some portions copied verbatim from): * Caffe Installation for Ubuntu * Running a Deep Learning Dream Machine »

The following post describes how to install TensorFlow 0.6 on an Amazon EC2 Instance with GPU Support. I also created a Public AMI (ami-e191b38b) with the resulting setup. Feel free to use it. UPDATED (28 Jan 2016): The latest TensorFlow build requires Bazel 0.1.4. Post now reflects this. Thanks to Jim Simpson for his assistance. UPDATED (28 Jan 2016): The AMI provided now exports env variables in ~/.bashrc. The following things are installed: »