Aditya A P's repositories
Capstone-Project-Unsupervised-ML-Topic-Modelling
The project explores a dataset of 2225 BBC News Articles and identifies the major themes and topics present in them. Topic Modeling algorithms such as Latent DIrichlet Allocation and Latent Semantic Analysis have been implemented. Effetiveness of the method of vectorization has also been explored
Investigation_of_CFD_methods_on_the_Lid-Driven_Cavity_Problem
A simple investigation into various CFD methods (like SF-Vorticity approach, primitive variable FDM, FVM etc.) by using the Lid-Driven Cavity problem as an example
Basic_Python_Script_in_ANSA_for_Automated_Handling_of_Skewed_Elements
Basic scripting in Python within the ANSA environment to remove bad quality surface mesh elements from the geometry (particularly, the skewed elements)
Capstone_EDA_Global_Terrorism_Analysis
A comprehensive analysis of the GTD, to uncover global terrorism patterns, trends, and impacts through data-driven analysis. Involves rigorous analysis of most used attack & weapon types; favourite targets; yearly distribution of casualties, no. of attacks, success rates, and more - both holistic and for specific countries and terror organizations
Observations_on_the_k-scheme_for_linear_Hyperbolic_PDE
basic investigation into the general k-scheme using the example of a simple linear hyperbolic 1D PDE
Airfoil_results_XFOIL
Visualisation of general XFOIL results
Capstone_Classification_Cardiovascular_Risk_Prediction
This project explores the Framingham Heart disease dataset with the objective to predict its risk in 10 years. Various methods for handling missing values and outliers are explored as iterations. After analysing the dataset, important and necessary features are selected. Seven ML models are implemented, with evaluation on the basis of Test Recall.
Capstone_Regression_NYC_Taxi_Trip_Duration_Prediction
This project aims to predict the Taxi-trip duration within NYC based on several factors as predictors. Various combinations of relevant features are explored as iterations. After analysing the dataset, important and necessary features are selected. Several regression models are implemented & evaluated based on R2 & RMSE, & predictions visualised
OSPL_Aeroacoustics
To understand OSPL, dB A-weightage etc.
Python_Map_Plotting
Plotting customized interactive maps using python roughly, as a temporary substitude to Tableau. Maharashtra state with district borders taken as an example