Assigned Monday, January 29
Thursday, February 1
Saturday, February 3
at 11:59 p.m.
First, download the file hackathon_3.ipynb. Then, go to crane.unl.edu and log in via two-factor authentication. You then need to select "Local Jupyter Notebook" and click "Upload" to upload hackathon_3.ipynb
The MNIST data and submission scripts are on crane in the folder
/work/cse496dl/shared/hackathon/03This folder contains the script run_py.sh for submitting optimization jobs to crane, as well as the example python script basic.py and sample output and log files job.out and job.err. Also in this folder is the subfolder mnist, which has four numpy files: mnist_test_images.npy, mnist_train_images.npy, mnist_test_labels.npy, and mnist_train_labels.npy. (These files are also zipped up in mnist.zip, but you should use the ones already on crane for this assignment.) The Jupyter Notebook for this hack-a-thon contains instructions for reading data from these files and partitioning the test files into validation and optimization sets.
Now you should be able to step through the notebook. When done, select "File" → "Close and Halt". Then check the box next to your notebook and click "Download". Then go to handin and submit your ipynb file by 11:59pm Thursday.
Last modified 01 February 2018; please report problems to sscott.