Rôles occupés
Miscellaneous
Back-end
Systems
Business Intelligence
Championed a dynamic Exploratory Data Analysis (EDA) using Python, pandas, and Matplotlib in Jupyter Notebook, extracting valuable insights from a
dataset encompassing 187 unique regions.
Harvested insights including number of confirmed, deaths, recovered cases region-wise, the Italy shown uppermost death cases of 27682.
Spain reported a robust recovery of 132,929 cases, followed by a meticulous identification and removal process for records based on specific criteria. This
process yielded a streamlined dataset, paving the way for comprehensive data processing and evaluation .
Employed Python and machine learning techniques to predict the likelihood of rock vs explosive outcomes. Dataset incorporated 111 mines & 97 rocks.
Achieved predictive accuracy rate of 76.2% enabling more informed decision- making in hazardous environments.
Applied a logistic regression model to address a binary classification problem, achieving a commendable test data accuracy rate of 83.4%.
Conducted data preprocessing and implemented train-test splitting, leveraging tools such as Python and machine learning with the sklearn library.