Due Date: 4/19/2016 (Thursday) 11:59 PM PST. Hard deadline: 4/22 (Sun) 11:59 PM PST with 3 late days
In this assignment we will familiarize you with basic concepts of neural networks, word vectors, and their application to sentiment analysis.
Note: Please be sure you have Python 2.7.x installed on your system. The following instructions should work on Mac or Linux. If you have any trouble getting set up, please come to office hours and the TAs will be happy to help.
Get the code: Download the starter code here and the complementary written problems here.
[Optional] virtual environment: Once you have unzipped the starter code, you might want to create a virtual environment for the project. 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 on your machine. To set up a virtual environment, run the following:
cd assignment1
sudo pip install virtualenv # This may already be installed
virtualenv .env # Create a virtual environment
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 environmentInstall requirements (without a virtual environment): To install the required packages locally without setting up a virtual environment, run the following:
cd assignment1
pip install -r requirements.txt # Install dependenciesDownload data: Once you have the starter code, you will need to download the Stanford Sentiment Treebank dataset. Run the following from the assignment1 directory:
cd cs224d/datasets
./get_datasets.shOnce you are done working, put the written part in the same directory as your IPython notebook file, and run the collectSubmission.sh script; this will produce a file called assignment1.zip. Rename this file to <your-sunet-id>.zip, for instance if your stanford email is jdoe@stanford.edu, your file name should be
cd cs224d/datasets
jdoe.zipStay tuned for a submission link, which will be posted here and on Piazza. For the written component, please upload a PDF file of your solutions to Gradescope. If you are enrolled in the class you should have been signed up automatically. If you added the class late or are not signed up, post privately to Piazza and we will add you to the roster. When asked to map question parts to your PDF, please map the parts accordingly as courtesy to your TAs. This is crucial so that we can provide accurate feedback. If a question has no written component (completely programatic), map it on the same page as the previous section or next section.
There will be four parts to this assignment. Each part has written and code components. The assignment is designed to be completed in order as later sections will leverage solutions to earlier parts. We recommend reading the assignment carefully and starting early as some parts may take significant time to run.