Predictive Analysis Course's notes for Computer Science B.S. at Ca' Foscari University of Venice

Dynamically route tasks to the best AI model and configuration using an LLM-powered intelligent selection system.

This is the website repository for the Stata packages lassopack & pdslasso. Please visit:

This project explores a Kaggle dataset to build predictive models for house prices. Includes data cleaning, EDA, feature engineering and model training using ensemble methods.

Cross-validation methods designed for ensemble learning

Maximum likelihood estimation for series system reliability with Weibull components under right-censoring and masked failure data, including likelihood ratio tests for model selection

My portfolio of algorithms I used to analysize various shapes and forms of data with statistical and machine learning tools.

Machine SurfLearning: Using Machine Learning Models to Predict San Diego Surf Conditions with Historical Buoy Data in Python

Curso de Regression Models do Coursera

Steps for preprocessing data for predictive modeling

Analysis of Categorical Variables

Prediction of the age of abalones in R.

Modeling and Prediction for Movies

Exercises from 'An Introduction to Statistical Learning with Applications in R' by James et al.

Intro to model selection in R lecture

A statistical and machine learning analysis of the Hitters dataset to model salary levels using multinomial logistic regression and other predictive techniques.

Built a system that can recognize words communicated using the American Sign Language (ASL). Trained a set of Hidden Markov Models (HMMs) using part of a preprocessed dataset of tracked hand and nose positions extracted from video to try and identify individual words from test sequences. Experimented with model selection techniques including BIC…

Model selection for reliability estimation in series systems with Weibull components: when can engineers safely use simpler models?