[ACL2023] We introduce LLM-Blender, an innovative ensembling framework to attain consistently superior performance by leveraging the diverse strengths of multiple open-source LLMs. LLM-Blender cut the weaknesses through ranking and integrate the strengths through fusing generation to enhance the capability of LLMs.

Comparison of classifier Algorithms on Diabetes Health Indicators Dataset.

Neural Networks ensemble via majority voting in order to classify ships given non-satellite images. All the models have been trained using PyTorch with pretrained weights.

This project aims to build a regression model that predicts the number of views for TED Talks videos on the TED website.

Regression-PrediksiHargaRumahBoston-kaggle-ensamblemodel-supervisedlearning

Various scripts for machine learning

Price prediction and appartments recommendation

Project on Trend Analysis on Pest Occurrence Using Meteorological Data - Information Systems and Business Intelligence (MEng), supervised by Prof. F. Amato, PhD A. Moccardi and PhD M. Fonisto (2024)

Comparison of classifier Algorithms on bank marketing Dataset

The AdaBoost (Adaptive Boosting) algorithm is a popular ensemble method used in machine learning to improve the performance of weak classifiers. It combines multiple weak classifiers to create a strong classifier, focusing more on the misclassified instances in each subsequent iteration.

Predicting potential donors using various machine learning models for Charity

This project employs machine learning algorithms to predict customer churn by analyzing historical customer data. It provides actionable insights to enhance customer retention. The models were fine-tuned using hyperparameter optimization and tackled data imbalance with SMOTE, achieving high F1-scores to drive targeted business strategies.

Random Forest library university project

Ensamble Voting for Financial Time Series

a classification problem using ensemble methods on the Titanic dataset.

This project is an end-to-end machine learning solution to predict student performance using key features like study time and test scores. It includes exploratory data analysis, model training, and a Flask-based web app for real-time predictions, all built with modular programming for clean and maintainable code.

Credit Risk Analysis utilizing imbalanced classification machine learning models

this repo is about the core machine learning algorithms built in core python and explained trough comments

Machine Learning assignments, Machine Learning (IE500618) course, fall 2022.

Project for Kernel-Based Machine Learning and Multivariate Modelling course at UPC Barcelona (FIB)