Classification: SVM Kernels
Published:
This notebook explores the usages of kernel functions in SVM classification. EE PMP 559, Spring 2019
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Notebooks
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Practical Classification: Support Vector Machines
Published:
This notebook explores the implementation of basic classification algorithms. EE PMP 559, Spring 2019
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Practical Classification: Logistic Regression
Published:
This notebook explores the implementation of basic classification algorithms. EE PMP 559, Spring 2019
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Regression and Time Series Prediction: Training and Testing
Published:
This notebook explores the application of regression to time series prediction. EE PMP 559, Spring 2019
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Linear Regression and DC Power Flow
Published:
This notebook explores the application of linear regression to state estimation in the DC power flow problem. EE PMP 559, Spring 2019
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L1, L2 Loss Functions and Regression
Published:
This notebook explores how choosing different loss functions influences the results of linear regression, and how to incorporate bias. EE PMP 559 Data Science for Power Systems, Spring 2019
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Linear Regression and Gradient Descent
Published:
This notebook is an self-assesment exercise in using Jupyter and NumPy tools to do basic linear regression for EE PMP 559 Data Science for Power Systems, Spring 2019.
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Visualizing curbside parking demand in Seattles Belltown neighborhhood
Published:
In this notebook we convert WSG84 latitude-longitudes to a 2-D web Mercator projection for the purpose of animating demand for curbside parking in downtown Seattle over time. The notebook can be viewed online and the full code and dataset can be downloaded below.
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