EE PMP 559 (Spring 2019): Data Science for Power Systems

This page contains links to all homework assignments and solutions as they are posted for EE PMP 559: Data Science for Power Systems. Homework assignments can be downloaded individually from https://github.com/cpatdowling/ee559 or they can pulled via a Git client. Git is a version control tool for software engineering, but is great for making your code available to a broader audience. If you’ve downloaded Git, to clone (initialize a repository and download) a repository from command line, say from your school directory for example:

chase@mycomputer:~/school$ git clone https://github.com/cpatdowling/ee559.git

When new assignments and solutions are released, all you need to do to update your repository is to use the ‘pull’ command inside the repository directory:

chase@mycomputer:~/school/ee559$ git pull

If you’d prefer to use a GUI, there is a desktop GitHub client that makes cloning, pushing, and pulling repositories very straightforward.

Submit your these coding assignments along with the written portions to the Dropbox links provided with your name in the .ipynb filename.

Assignment 7: Practical Classification: Support Vector Machines

Due: Saturday 5/25 at 11:00 PM. Submit here

view web version, source

Assignment 6: Practical Classification: Support Vector Machines

Due: Saturday 5/18 at 11:00 PM. Submit here

view web version, source

Assignment 5: Practical Classification: Logistic Regression

Due: Saturday 5/11 at 11:00 PM. Submit here

view web version, source

Assignment 4: Regression and Time Series Forecasting: Training and Testing

Due: Thursday 5/2 at 11:00 PM. Submit here

view web version, source

Assignment 3: Linear Regression and DC Power Flow

Due: Thursday 4/25 at 11:00 PM. Submit here

view web version, source

Assignmnet 2: L1, L2 Norms, Bias, and Regression

Due: Thursday 4/18 at 11:00 PM. Submit here

Homework questions can again be found at the bottom of the notebook where you will insert your own code. Please include your discussion in comments and/or generate plots where prompted. The class repo also contains some data required for the assignment. view web version, source

Assignment 1: Linear Regression and Gradient Descent

Due: Thursday 4/11 at 11:59 PM. Submit here

Download the assignment notebook; homework questions can be found at the bottom of the notebook where you can insert your own code. The executable code should include comments with your discussion and/or generate plots where prompted. The class repo also contains some data required for the assignment in a txt file. view web version, source