[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

Price prediction and appartments recommendation

Various scripts for machine learning

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

Random Forest library university project

Ensamble Voting for Financial Time Series

Credit Risk Analysis utilizing imbalanced classification machine learning models

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.

Applied numerous algorithm models to solve a binary classification problem of predicting if any given prospective customer converts to a sale, through the company’s online sales channel.

Application of Machine and Deep Learning techniques on images and texts.

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

a classification problem using ensemble methods on the Titanic dataset.

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

finding_donors machine learning model