Welcome to Machine Learning for Insurance: Predict Claim & Assess Risk course. This is a comprehensive project based course where you will learn how to build insurance risk assessment models, predict insurance claim amounts, and detect insurance claim fraud using models like XGBoost, LightGBM, Random Forest, Logistics Regression, SVM, and KNN. This course is a perfect combination between machine learning and risk assessment, making it an ideal opportunity to level up your data science skills while improving your technical knowledge in insurance business. In the introduction session, you will learn about machine learning applications in insurance and also its technical limitations.
Then, in the next section you will learn how insurance risk assessment models work. This section will cover data collection, data preprocessing, feature selection, splitting data into training and testing sets, model selection, model training, assessing risk, and model evaluation. Afterward, you will download insurance datasets from Kaggle, it is a platform that provides many high quality datasets from various industries.
- Learn about machine learning applications in insurance and its technical limitations
- Learn how to predict insurance claim amount using XGBoost
- Learn how to build insurance risk assessment model using Logistic Regression
- Learn how to detect insurance claim fraud using Support Vector Machine
- Learn how to predict insurance claim amount using LightGBM
- Learn how to build insurance risk assessment model using Random Forest Classifier
- Learn how to detect insurance claim fraud using K Nearest Neighbor
- Learn how to test machine learning model using synthetic data
- Learn how to handle class imbalance using Synthetic Minority Oversampling Technique
- Learn how to conduct feature importance analysis using Random Forest Regressor
- Learn how to analyze relationship between age, gender, and insurance claim amount
- Learn how to find correlation between body mass index and blood pressure with insurance claim amount
- Learn how to find correlation between smoking status and insurance claim amount
- Learn how insurance risk assessment models work. This section covers data preprocessing, feature selection, train test split, model training, and assessing risk
- Learn how to clean dataset by removing missing values and duplicates
