missing-values-analysis

Performing multiple logistic regression analysis on airline and customer data to predict the satisfaction. 🔵R

Predicting the cab booking using ML algorithms by considering the various conditions of seasons, day timing, & environment

Comparing the performances of simple linear, multiple linear, multi-layer perceptron and k-nearest neighbors regressions on abalone data to predict the age.

Estimation of vital status of patients with ovarian cancer using Machine Learning models

Python examples of data wrangling and analysis, including data cleaning, transformation, handling missing values, and exploratory insights.

Perform Exploratory Data Analysis(EDA) on loan applications to understand how various client attributes (like marital status, education, occupation, etc.) influence the tendency of default.

Testing variables for multicollinearity, multivariate normality and analyzing outliers and missing values. ⭕SPSS 🔵R