Setup Instructions
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Setup Instructions
Setup
You can work on the assignment in one of two ways: locally on your own machine, or on a
virtual machine on Google Cloud.
Working remotely on Google Cloud (Recommended)
Note:Note: after following these instructions, make sure you go to Download dataDownload data below (you can
skip the Working locallyWorking locally section).
As part of this course, you can use Google Cloud for your assignments. We recommend this
route for anyone who is having trouble with installation set-up, or if you would like to use better
CPU/GPU resources than you may have locally. Please see the set-up tutorial here for more
details. :)
Working locally
Installing Anaconda:Installing Anaconda: If you decide to work locally, we recommend using the free Anaconda
Python distribution, which provides an easy way for you to handle package dependencies.
Please be sure to download the Python 3 version, which currently installs Python 3.6. We are
no longer supporting Python 2.
Anaconda Virtual environment:Anaconda Virtual environment: Once you have Anaconda installed, it makes sense to
create a virtual environment for the course. If you choose not to use a virtual environment, it is
up to you to make sure that all dependencies for the code are installed globally on your
machine. To set up a virtual environment, run (in a terminal)
conda create -n cs231n python=3.6 anaconda
to create an environment called cs231n .
CS231n Convolutional Neural Networks for Visual Recognition
cs231n
cs231n
karpathy@cs.stanford.edu
Then, to activate and enter the environment, run
source activate cs231n
To exit, you can simply close the window, or run
source deactivate cs231n
Note that every time you want to work on the assignment, you should run source activate
cs231n (change to the name of your virtual env).
You may refer to this page for more detailed instructions on managing virtual environments
with Anaconda.
Python virtualenv:Python virtualenv: Alternatively, you may use python virtualenv for the project. To set up a
virtual environment, run the following:
cd assignment1
sudo pip install virtualenv # This may already be installed
virtualenv -p python3 .env # Create a virtual environment (python3)
# Note: you can also use "virtualenv .env" to use your default python (please note we support 3.6)
source .env/bin/activate # Activate the virtual environment
pip install -r requirements.txt # Install dependencies
# Work on the assignment for a while ...
deactivate # Exit the virtual environment
