Explore my Projects 

This project delves into the realm of diabetes diagnosis, employing a sophisticated machine learning approach centered around logistic regression. Through the utilization of this powerful statistical model, the aim is to analyze and interpret patient data, facilitating accurate predictions for the presence of diabetes. The focus on logistic regression ensures a robust and interpretable framework, contributing to the development of a reliable diagnostic tool for improved healthcare outcomes.

The objective is to accomplish the task by employing a fitting multiple linear regression model. The response variable in question is the Count of total rental bikes, with predictors identified through logical and statistical methods.

Played a pivotal role in a research project "Developing Companion Robot for Reducing Stress and Increasing Workability" focused on developing a companion robot to reduce stress and enhance workability. Conducted in-depth statistical analysis of the research results, employing various data analysis techniques and tools. Provided valuable insights and data-driven conclusions that contributed significantly to the project's success.

This project delves into a synthetic advertising dataset, employing logistic regression to predict user clicks on a company website's ads. Key features such as 'Daily Time Spent on Site,' 'Age,' and 'Daily Internet Usage' are analyzed, enhancing our understanding of user behavior and aiding in targeted advertising strategies.

Dive into the Support Vector Machine (SVM) project dissecting the famous iris dataset. This analysis unravels intricate patterns and harnesses SVMs to provide insightful conclusions about the underlying botanical data.