Modeling ship performance curves to reduce fuel consumption

The Google Advanced Data Analytics Certificate contains information on how to use machine learning, predictive modeling, statistical techniques, and experimental design to collect and analyze large amounts of data.

This project focuses on automating the analysis and reporting of bibliometric data, specifically targeting the annual production of academic articles. The primary goal is to understand trends, anomalies, and patterns in bibliometric data through a combination of statistical modeling and exploratory data analysis.

Beer sales price regression in python

Developed a linear regression model to forecast case shipments considering various predictor variables such as time trends (month), seasonality (seasonal index), and promotions. Conducted Durbin Watson test and generated a forecast and prediction interval.

Regression Modeling in Practice - Gapminder studies - Coursera

This project implements a Flask web app for predicting Boston house prices using a stacked ensemble model with Random Forest and XGBoost. The machine learning solution is trained on a dataset featuring various housing-related features.