Python package for Bayesian Model Mixing

Slides, exercises, and exams for my course "Statistical Learning with R" (Ecole Normale Supérieure Paris-Saclay, 2023)

ML projects, which I worked on utilising different machine learning algorithms.

A portfolio of machine learning algorithms that are essential and commonly used.

Forecasted product sales using time series models such as Holt-Winters, SARIMA and causal methods, e.g. Regression. Evaluated performance of models using forecasting metrics such as, MAE, RMSE, MAPE and concluded that Linear Regression model produced the best MAPE in comparison to other models

Machine learning project that predicts the percent change in stock price after next earnings event for public companies. Completed as a Riipen Data Science Internship.

A Machine Learning exploration evaluating various models to predict Airbnb prices, culminating in an optimized Gradient Boosting Regressor.

[ Machine Learning ] 1st Practice re-uploaded. Co-Author: @Devinchy

MF-BAVART model introduced in "Nowcasting in a Pandemic using Non-Parametric Mixed Frequency VARs"

🎓 Curso com os criadores do Scikit-Learn

Repository showcasing a collection of diverse regression analysis projects including salary prediction and more.

Workflow to spatially predict mud (silt and clay) content of seafloor surface sediments in Norway

Tip-Prediction-for-New-York-Uber/Lyft-Drivers

[ICML23] Extrapolated Random Tree for Regression

Using Python and the Natural Resources Canada Fuel Consumption Ratings to view and predict vehicle efficiency.

Decision Tree to predict the value of a continuous target variable

Project about the use of Supervised (Machine) Learning techniques to predict the popularity of a tweet about food.