- House Price Advanced Regression Techniques by Kaggle (Python ,Lasso ,XG-Boost):
● Identified the important features from 79 Explanatory variables describing every aspect of residential homes by conducting exploratory Data Analysis. Performed various algorithms like Lasso, Ridge, Elastic net, Gradient Boosting Regressor to predict the housing prices.
● Increased Accuracy by using logarithmic functions to normalize the data and increased the accuracy by 20% by using Lasso. Predicted the house prices with a value of 0.11802 RSMLE.
- Titanic Survival Prediction by Kaggle (Python ,XG-Boost ,Random Forest)
•Identified factors affecting the Survival Rate of Passengers & performed algorithms like Regression, Random Forest
•Performed feature Engineering & set right parameters for hyperparameter tuning predicted the survival rate & got accuracy of 0.81%
- Credit Card Fraud Detection(Python ,Random Forest)
•Detected the number of false credit card transactions on the dataset by performing Data Visualization, pattern formation & normalized data.
•Build Logistic & Random Forest Classification models & optimized the model getting an accuracy of 0.99%