StephenGenusa/ai-ensemble-suite

Python framework for multiple GGUF language models to collaborate on tasks using structured communication patterns, aggregating their outputs into coherent responses

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usgs/pestpp

tools for scalable and non-intrusive parameter estimation, uncertainty analysis and sensitivity analysis

Language: C++ - Size: 1.09 GB - Last synced at: 3 days ago - Pushed at: 14 days ago - Stars: 146 - Forks: 79

Curt-Park/handwritten_digit_recognition

Handwritten digit recognition with MNIST & Keras

Language: Python - Size: 40.5 MB - Last synced at: 8 days ago - Pushed at: over 4 years ago - Stars: 78 - Forks: 31

zainabja52/Machine-Learning-and-Data-Science

This repository contains machine learning and data science projects completed as part of academic coursework and practical exploration. It focuses on implementing and comparing algorithms like K-Nearest Neighbors (KNN), Logistic Regression, Support Vector Machines (SVM), and Ensemble Methods for classification and regression tasks.

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ZhiningLiu1998/self-paced-ensemble

[ICDE'20] ⚖️ A general, efficient ensemble framework for imbalanced classification. | 泛用，高效，鲁棒的类别不平衡学习框架

Language: Python - Size: 1.44 MB - Last synced at: 16 days ago - Pushed at: about 1 year ago - Stars: 257 - Forks: 50

sulis-hpc/sulis-hpc.github.io

User documentation website for the Sulis tier 2 HPC service. Built using Jekyll.

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N00Bception/AI-CryptoTrader

AI-CryptoTrader is a state-of-the-art cryptocurrency trading bot that uses ensemble methods to make trading decisions based on multiple sophisticated algorithms. Built with the latest machine learning and data science techniques, AI-CryptoTrader provides a powerful toolset and advanced trading stratgies for maximizing your cryptocurrency profits.

Language: Python - Size: 3.1 MB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 61 - Forks: 19

powell-clark/supervised-machine-learning

Mathematical theory, code examples, and production implementations of classification, regression, trees, SVMs, ensemble methods, and neural networks

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ChaitanyaC22/Udacity-AWS-MLE-ND-Project1-Bike-Sharing-Demand-with-AutoGluon

This project focuses on using the AWS open-source AutoML library, AutoGluon, to predict bike sharing demand using the Kaggle Bike Sharing demand dataset.

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ikanurfitriani/Final-Project3-EnsembleMethod-RF

This repository contains code archives for models that predict the risk of death from heart failure.

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karimosman89/credit-scoring

Evaluate the creditworthiness of individuals.Develop a credit scoring model that evaluates the creditworthiness of individuals based on historical data.Help financial institutions assess risk more accurately.

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Aditya1Jhaveri/Cervical-Cancer-Image-Classification-in-Deep-Learning

This repository hosts the Cervical Cancer Image Classification project, a comprehensive effort aimed at improving the classification accuracy of Squamous Cell Carcinoma (SCC) through advanced deep learning models and ensemble techniques. The project utilizes the Herlev dataset.

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course-files/BBT4206-Lab10of15-EnsembleMethods-R

Instructional materials (course files) for the BBT4206 course (Business Intelligence II) using R. Topic: Ensemble Methods.

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LinggarM/Ensemble-Learning-Comparison-on-Diabetes-Classification

Comparison of ensemble learning methods on diabetes disease classification with various datasets

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Parin30/AI-ML-Projects

A collection of AI and ML projects demonstrating various techniques, algorithms, and applications.

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jasminenalani/JDAY-Stat228-Final

My Final Project for my Introduction to Data Science course at Simmons University.

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YisongMiao/CS5228-project

Winning 2nd place🥈at NUS CS5228 in-class Kaggle competition 2018!

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MichaelHager01/Decision-Trees-and-Ensemble-Methods

This is an assignment from my Machine Learning for Mechanical Engineers course that demonstrates an understanding in decision trees and ensemble methods using scikit-learn.

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nanditashukla/AIML-Projects

Projects completed as a part of IIIT-Delhi's Post Graduation Diploma in Computer Science and Artificial Intelligence.

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victorsemeraro/Optimization

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ayigitdogan/BandB-Data-Analysis-Case-Study

My solutions to the data analysis and forecasting case study held by Bella & Bona

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devanshkhare1705/Personalizing-K12-Education

Using deep learning to predict whether students can correctly answer diagnostic questions

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Cimm-Yeoman/Divorce-Prediction

The goal of this report was to identify which variable best predicts divorce using decision trees and other ensemble methods. In the data set, Class is the response variable, with 0 = still married and 1 = divorced.

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FlorinAndrei/timeseries-forecasting-fourier-time-dummies

Time series forecasting with Fourier-adjusted time dummies

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thomas-brink/STATS315B_Project

Course project for Stanford's STATS 315B (Modern Applied Statistics: Learning II).

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FlorinAndrei/predict-sale-prices-regression

Predict sale prices via regression models, using PCA, k-means clustering, ensemble models, pipelines, etc.

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STProgrammer/Ensembled-naive-bayes-classifiers

Test and comparison of ensemble method with naive bayes classifier on 5 different data sets.

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wwweiwei/Track2Vec

Official Implementation of Track2Vec: Fairness Music Recommendation with a GPU-Free Customizable-Driven Framework EvalRS-CIKM-2022

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agusticonesagago/Evaluation-of-methods-to-combine-predictions-from-ensemble-learning-in-multivariate-forecasting

This project studies different possibilities to make good predictions based on machine learning algorithms, but without requiring great theoretical knowledge from the users. Moreover, a software package that implements the prediction process has been developed. The software is an ensemble method that first predicts a value taking into account different algorithms at the same time, and then it combines their results considering also the previous performance of each algorithm to obtaina final prediction of the value. Moreover, the solution proposed and implemented in this project can also predict according to a concrete objective (e.g., optimize theprediction, or do not exceed the real value) because not every prediction problem is subject to the same constraints. We have experimented and validated the implementation with three different cases. In all of them, a better performance has been obtained in comparison with each of the algorithms involved, reaching improvements of 45 to 95%.

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LeondraJames/AdClick_Fraud

Capstone project #2 for the Harvard University Professional Certificate in Data Science

Language: R - Size: 888 KB - Last synced at: almost 2 years ago - Pushed at: about 6 years ago - Stars: 2 - Forks: 0

Otniel113/LungCancerIdentification

Identifikasi kanker paru-paru pada perokok menggunakan Metode Ensemble berdasarkan Data Ekspresi Gen

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ajayarunachalam/metaEnsembleR

Intuitive Package for Heterogeneous Ensemble Meta-Learning (Classification, Regression) that is fully-automated

Language: R - Size: 502 KB - Last synced at: 2 months ago - Pushed at: over 4 years ago - Stars: 0 - Forks: 0