Feature engineering and data preparation on Delhivery logistics data to create modeling-ready features for delivery time and operational analysis.
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Updated
Feb 2, 2026 - Jupyter Notebook
Feature engineering and data preparation on Delhivery logistics data to create modeling-ready features for delivery time and operational analysis.
Comprehensive benchmark of PCA, Kernel PCA and t-SNE on the MNIST dataset with dimensionality reduction, image reconstruction, visualization and classification analysis.
Apprenticeship project with Indian Institute of Science. Objectives were to Model tumor and immune cell interaction in the presence of MMP & TIMP by varying their diffusion rates and check the effect of MMP8 on these interactions. These simulations provides insights into how ECM remodelling shapes cancer progression.
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