A Data Engineering project where we create a data model programatically using Python on PostgreSQL and load data onto it using Pandas.
A Machine Learning project using K-Means Clustering for grouping the customers of a shopping mall based on their spending habits.
A Machine Learning model using Linear Regression & XGBoost Regressor for predicting the Medical Insurance cost for an individual.
A Machine Learning project using Logistic Regression for predicting whether a credit card transaction is fraudulent or not.
A Machine Learning project using Logistic Regression for predicting whether a person is at risk of having a heart disease or not.
A Machine Learning project using Linear & Lasso Regression for predicting the price of used car.
A Machine Learning project using RandomForest Classifier for predicting the quality of wine.
A Machine Learning project using Logistic Regression for predicting whether a news is fake or real.
A Machine Learning project using XGBoost Regressor for predicting house prices.
A Machine Learning project using SVM for predicting whether a person is diabetic or non diabetic.
A Python module for extracting keys from a YAML file. If a YAML contains a nested hierarchy then the complete path is listed from parent to child key.
In this project we perform A/B Testing for an E-Commerce website and try to predict whether the old or the new page is better.
