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Solutions for CS231n course from Stanford University: Convolutional Neural Networks for Visual Recognition

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CS231n: Convolutional Neural Networks for Visual Recognition

These past weeks I've spent several weeks on the CS231n course from Stanford University. Here are my solutions to the assignments. These solutions are for the 2016 version of the course. Apparently, the 2017 version is similar besides the fact that they finally use Python 3.5!

Installation

  1. Install Anaconda
  2. go to assignmentX where X is either 1, 2, 3 using a Terminal:
    $ cd \path\to\assignment1
  3. create a python 2.7 environnment using
    $ conda env -n cs231n python=2.7 anaconda
  4. activate your environment using (add source before activate if you're working with Linux/Mac)
    $ activate cs231n
  5. install the dependencies using requirements.txt
    $ pip install -r requirements.txt
  6. Launch notebook using:
    $ jupyter notebook name_of_notebook.ipynb

Note

I wrote several blog posts accessible from my website if you want to understand in detail how the code works.

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Solutions for CS231n course from Stanford University: Convolutional Neural Networks for Visual Recognition

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