Regression
This is my note for ISYE 8803. This course focuses on analysis of high-dimensional structured data including profiles, images, and other types of functional data using statistical machine learning. A variety of topics such as functional data analysis, image processing, multilinear algebra and tensor analysis, and regularization in high-dimensional regression and its applications including low rank and sparse learning is covered. Optimization methods commonly used in statistical modeling and machine learning and their computational aspects are also discussed.
gatech
polynomial_regression /
splines /
knn /
regression /
rbfkernel /
pca /
image_analysis /
transformation /
convolution /
segmentation /
kmeans /
clustering /
sobel_operator /
kirsch_operator /
tensor_data_analysis /
kronecker_product /
khatri_rao_product /
hadamard_product /
tucker_decomposition /
optimization /
regularization /
ridge /
lasso
Analytics is extremely relevant in all aspects of ride-hailing. In this project, I merely covered a few use cases, with one or two relevant models. Even with this brief exploration, I can conclude that analytics can lead to better outcomes for both drivers and passengers.
georgia tech /
data viz /
analytics /
tootle
analytics in ride sharing /
tootle /
nepal /
analytics /
isye-6501 /
ride hailing /
ride sharing /
regression /
optimization /
eda