CSCI 373: Lab Exercises

Most weeks, we will use our Monday class time to practice valuable skills for applying machine learning to real-world problems through hands-on practice with lab exercises in King 135/137. The instructions for starting each lab will be provided below.

Instructions for using GitHub for our lab exercises can be found on the Resources page of the class website, as well as using this link.

We will be using the Linux operating system on the lab machines. Instructions for logging into Linux will be provided within Lab 1. I would suggest creating a folder (e.g., called CSCI373) in your user directory to store your cloned repositories for each lab (and also the homework assignments that you want to run on the machines in the computer labs).

Lab 1: Python Libraries

Date: September 9
URL: https://classroom.github.com/a/Yk1cb_bA
Due: September 15 (11:59 PM)

Lab 2: pandas and scikit-learn

Date: September 23
URL: https://classroom.github.com/a/iy-GqT2Y
Due: September 29 (11:59 PM)

Lab 3: Data Visualization with plotnine

Date: September 30
URL: https://classroom.github.com/a/EDPBxn0p
Due: October 6 (11:59 PM)

Lab 4: Data Transformations

Date: October 7
URL: https://classroom.github.com/a/olZ-r8v2
Due: October 13 (11:59 PM)

Lab 5: Feature Selection

Date: October 14
URL: https://classroom.github.com/a/tGCFvmvX
Due: October 27 (11:59 PM)

Lab 6: Hyperparameter Tuning

Date: October 28
URL: https://classroom.github.com/a/qojoPWAc
Due: November 3 (11:59 PM)

Lab 7: Neural Networks with PyTorch

Date: November 4
URL: https://classroom.github.com/a/Pp9RmmyO
Due: November 17 (11:59 PM)

Lab 8: Convolutional Neural Networks (CNNs)

Date: November 25
URL: https://classroom.github.com/a/PJHPrJ_b
Due: December 11