/ML-featureselection-regression

Assignment from ML class at GA Tech (CS 7641): to implement feature selection, PCA, and regression methods.

Primary LanguageJupyter Notebook

CS 7641 - Spring 21 - HW3: Image Compression with SVD, PCA, Polynomial Regression, Naive Bayes

Setup

  1. Install Miniconda if you do not already have it installed.
  2. Create an conda environment from the .yml files given. If you are running windows, use the Conda Prompt, on Mac or Linux you can just use the Terminal. Make sure to modify the command based on your OS (linux, mac, or win): conda env create -f ml_hw3_env_<OS>.yml
  3. This should create an environment named 'ml_hw3'. Activate it using the Windows command, activate ml_hw3 or the MacOS / Linux command, conda activate ml_hw3
  4. Run the notebook using jupyter notebook hw3_code/hw3.ipynb or jupyter lab hw3_code/3.ipynb
  5. Generate the zip folder to turn into gradescope by running bash collect_submission.sh. This will automatically select the required python scripts to turn in as well as convert your jupyter notebook to a pdf to turn in additonally.