In the employee attrition dataset, employing Support Vector Machine (SVM) with SVMradial for accuracy involves thorough Exploratory Data Analysis, including Descriptive Statistics, Measures of Frequency, Central Tendency, Distribution, and Relationship. Inferential Statistics and Basic Visualization follow, utilizing Univariate and Multivariate Plots. Preprocessing involves a Heatmap of missing data, Data Transformation, Scaling, Centering, and Standardization. Training Models includes dataset splitting and employing algorithms like Naive Bayes, LDA, and SVM with repeated k-fold Cross Validation. Model performance is assessed, followed by Hyperparameter Tuning through Grid Search and Ensemble methods like Boosting and GBM. The model is saved and loaded for predictions, with deployment options including a Plumber API and a Customer-facing Dashboard for user-friendly insights