Predictive Analysis Course's notes for Computer Science B.S. at Ca' Foscari University of Venice
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Updated
Jul 17, 2025 - HTML
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
My portfolio of algorithms I used to analysize various shapes and forms of data with statistical and machine learning tools.
Maximum likelihood estimation for series system reliability with Weibull components under right-censoring and masked failure data, including likelihood ratio tests for model selection
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.
Exercises from 'An Introduction to Statistical Learning with Applications in R' by James et al.
Modeling and Prediction for Movies
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.
Boston house prices prediction for machine learning nanodegree
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…
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