agrawal-priyank/machine-learning-regression
Built house price prediction model using linear regression and k nearest neighbors and used machine learning techniques like ridge, lasso, and gradient descent for optimization in Python
Implements polynomial regression alongside linear variants and uses GraphLab Create for direct algorithm application, complementing hand-coded gradient descent implementations. Feature selection via L1/L2 regularization directly addresses multicollinearity and overfitting across simple, multiple, and polynomial regression architectures. Jupyter notebooks provide modular, reproducible workflows organized by algorithmic approach rather than a single integrated pipeline.
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Dec 08, 2023
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