Machine Learning in R : Support Vector Machines

Learn Machine Learning in R: Build a Loan Approval Prediction Model with Support Vector Machines

Master the power of the R programming language by building a complete machine learning project that predicts loan approvals using Support Vector Machines (SVM). Throughout this hands-on course, you'll learn the end-to-end machine learning workflow—from data exploration and cleaning to feature engineering, model building, and evaluation.

Using a real-world loan dataset, you'll discover how machine learning can help financial institutions make faster, more consistent, and data-driven lending decisions. By applying practical techniques to real data, you'll gain valuable experience that can be transferred to many other classification problems.

Why Take This Course?

This project-based course is designed for students, aspiring data scientists, and developers who want practical experience building machine learning models in R. Rather than focusing only on theory, you'll follow a step-by-step approach to create a complete loan approval prediction system from scratch.

Working with a dataset containing 614 loan applications, you'll analyze features such as gender, marital status, education, applicant income, loan amount, credit history, and more to train an accurate classification model. Along the way, you'll learn essential data preprocessing and feature engineering techniques used in real-world machine learning projects.

What You'll Learn

• Understand the fundamentals of Support Vector Machines (SVM)

• Perform Exploratory Data Analysis (EDA)

• Handle missing categorical and numerical values

• Clean and prepare data for machine learning

• Build and train an SVM classification model in R

• Improve model performance through feature selection

• Evaluate and interpret machine learning results

• Apply a complete end-to-end machine learning workflow

By the end of this course, you'll have built a complete loan approval prediction project in R and gained practical machine learning skills that you can apply to finance, banking, and many other real-world classification problems. Enroll today and start building industry-relevant ML projects with confidence.