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CPSC392ParlettPelleriti

Readings (optional, all books free)

Topic PDSH ISLP ESL
Pandas/Numpy Chapters 2,3 Chapters 2.3.3
Visualization Chapter 4 (mpl, sb) Chapters 2.3.4 (mpl)
Linear Regression Chapters 5.3, 5.6 Chapters 2.2.2, 3, 5 Chapters 2.3.1, 3.2, 7.2, 7.3, 7.10
LASSO/Ridge (Regularization) Chapter 5.6 Chapter 6.2 Chapter 3.4, 3.8
Logistic Regression Chapter 4.3 Chapter 4.4
Decision Trees/Tree Based Models Chapter 5.8 Chapter 8.1, 8.2 Chapters 9.2, 10.10.2, 15
Naive Bayes Chapter 5.5 Chapter 4.4.4
K-Nearest Neighbors Chapter 2.2.3 Chapters 2.3.2, 13.3
K-Means/Gaussian Mixture Models Chapters 5.11, 5.12 Chapters 12.4.1, 12.4.3 Chapters 8.5, 13.2.1, 13.2.3, 14.3.6, 14.3.7
DBSCAN
Hierarchical Clustering Chapter 12.4.2 Chapter 14.3.12
Principal Component Analysis Chapter 5.9 Chapter 6.3.1, 12.2 Chapter 14.5.1
Neural Networks Chapter 10 Chapter 11

Resources

  • Lecture Playlist
  • Google Colab: a shareable online jupyter notebook. Like google docs for code (but instead of being able to see changes live, you can only see other people's changes when you save and re-open notebook). Great for collabing with other people, or for storing your code online.
  • OBS Streamlabs: Great for recording your presentation.
  • Slack: A place to ask me questions, meet with other students, share fun data sets...etc.
  • HP Smart Apple Android: An app that will let you "scan" things to PDF using the camera on your phone/tablet. Great for sending me signed documents, or other important files.

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