An end-to-end data science project presented on a static HTML/CSS platform. Analyzes 28,470 California DMV records (2021–2025) using Poisson and logistic regression to examine disengagement rates across manufacturers, environments, and event categories, translating the results into recommendations for AV manufacturers and transportation regulators.
TDD Junit 5, aserciones, suposiciones, ciclo de vida de los test, pruebas parametrizadas y Hamcrest - ValueSource
This data science project focuses on analyzing customer sentiment and booking patterns for British Airways flights. It combines web scraping, Natural Language Processing (NLP), data visualization, and machine learning to extract actionable insights.
This project was done in the 4th semester of Btech data science. Took an online dataset about cars. Understood, cleaned, visualized and prepared our data for building a regression model. Using Recursive feature elimination and Backward selection as a method of feature selection we built a final model. Then tested the assumptions that we made abo…
Written various types of JUnit test cases using Assertion and Assumption methods.
Analysis of real estate sales data. Tasks include understanding dataset structure, variable conversion, descriptive analysis, pairwise comparisons, linear relationship analysis, multiple regression modeling, feature selection using stepwise methods, final model summary, assumptions checking, and LASSO variable selection. Results are documented.
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