MAvRK7/Malware-detection-using-MLmodels

This repo is about the cyber security project where malware is detected and classified

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ahmedshahriar/Telco-Customer-Churn-Prediction-Streamlit-App

This streamlit app predicts the churn rate using Gradient Boosting models (XGBoost, Catboost, LightGBM) on IBM Customer Churn Dataset

Language: Python - Size: 1.32 MB - Last synced at: 7 days ago - Pushed at: about 1 year ago - Stars: 3 - Forks: 3

suraj5424/Stacking-library

A powerful ensemble learning class that supports multi-layer stacking and blending models for regression tasks, with K-fold cross-validation and hold-out validation set options, for robust model performance.

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Alex-Lekov/AutoML_Alex

State-of-the art Automated Machine Learning python library for Tabular Data

Language: Python - Size: 25.9 MB - Last synced at: 16 days ago - Pushed at: over 1 year ago - Stars: 229 - Forks: 43

Daniil-Horobets/Credit-Card-Approval-Prediction-100

Credit Card Approval Prediction 100%. This Credit Risk Classification Model predicts whether a loan applicant is "good" or "bad" using a stacking ensemble of Random Forest, XGBoost, and CatBoost with logistic regression. It handles imbalanced data with SMOTE and extracts key financial insights through feature engineering.

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business-science/modeltime.ensemble

Time Series Ensemble Forecasting

Language: R - Size: 21.2 MB - Last synced at: 14 days ago - Pushed at: 9 months ago - Stars: 78 - Forks: 18

Ankitjha2202/Wind-power-prediction

Wind Power Prediction using Stacking Ensemble Machine Learning Algorithm

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sibirbil/LESS

Learning with Subset Stacking

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minakdr/Car-price-prediction-using-Stacking-ensemble-modeling-technique

This project aims to predict the selling prices of used cars based on various features such as brand, model year, mileage, and engine specifications.using-Stacking-ensemble-modeling-technique

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Dalageo/ML-TitanicShipwreck

Exploring the World's Most Renowned Shipwreck 🚢

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EricaYanoshak/AI-Purchase-Behavior-Project

This project focuses on predicting customer purchase behavior using machine learning models, with an emphasis on feature importance.

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habedi/stacking-framework-for-lwpwq-kc

A stacking framework for the Linking Writing Processes to Writing Quality Kaggle competition

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Pythondeveloper6/Ensemble-learning-beginner-guide

machine learning ensemble learning types in easy steps with examples

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prneidhardt/Ensemble-Learning

EasyVisa Project

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BernardoRaimundo/Credit-Risk-Scoring-A-Stacking-Generalization-Approach

Ensemble based approach compared to traditional machine learning models

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nhtlongcs/cassava-leaf-disease-classification

Identify the type of disease present on a Cassava Leaf image

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gaellinkeu/ML-on-Titanic-Data

Titanic Challenge using different Machine Learning models

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manjugovindarajan/EasyVisa-US-visa-applicant-profiling-using-ML

Analyze data of US work Visa applicants, build a predictive model to facilitate approvals, and based on factors that significantly influence visa status, recommend profiles for whom visa should be certified or denied.

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marielgyap/Spot-the-Hits

My capstone project for the Institute of Data investigates the metadata of songs on Spotify, building a predictive model to project a track's popularity on Spotify using its audio features.

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CostiaB/Task-Mate-Kenyan-Sign-Language-Classification-Challenge

Stacking model for sign language images

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RichaSavant/Stock-Market-Analysis-A-Two-Stage-Comparative-Stacking-Approach-using-Pyspark-Jan_2024

This project aims to enhance the accuracy and efficiency of stock market predictions by employing a sophisticated machine learning methodology. This project leverages the power of PySpark, a robust framework for distributed data processing, to handle large datasets and perform complex computations.

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tboudart/Tanzanian-Water-Pumps-Clustering-and-Classification

For this group project, I performed cluster analysis and classification using Python to predict one of three classes for water pumps; functional, functional but needs repair, and non-functions. I used clustering to find hidden data structures to exploit for fitting individual classification techniques with better results than using the entire dataset. Unfortunately, k-means clustering, DBSCAN, hierarchical clustering, nor OPTICS produced well-defined clusters. The entire dataset was therefore used for fitting classification algorithms. The two classification techniques I was responsible for were k-nearest neighbors and stacked generalization ensemble. For the latter, I combined the best models each group member developed. All the models had a hard time predicting the functional but need repair class. My best model was only able to achieve an accuracy of 76%.

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KanikaGaikwad/Detect-AI-Generated-Text-

This project addresses the challenges of AI-generated content, such as misinformation and bias, by developing a machine-learning algorithm that distinguishes between AI-generated and human-generated texts. This solution enhances content authenticity and mitigates associated risks.

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VasilikiZarkadoula/Machine-Learning-Auth-2021

Εxercises for Machine Learning course in Faculty of Informatics of Aristotle's University of Thessaloniki

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pouryahoseini/Convolutional-Stacking-Network

A deep convolutional network made of stacked feature extractors

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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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Bernardbyy/SpotifyMusicClassifier

Spotify Music Classifier with Machine Learning Using Spotify API

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ramongss/2020-IEEE-BitcoinPrice

:moneybag: Multi-step ahead Bitcoin price forecasting based on VMD and ensemble learning methods | :sunny: Solar power forecasting based on ensemble learning methods

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mohit01-10/Alzheimer-s-Disease-Classification-using-Stacking-Ensembling

This project is dedicated to accurately classify Alzheimer's disease into Demented, Non-demented and Converted Category.

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LuluW8071/Laptop-Price-Prediction

A collection of machine learning models for predicting laptop prices

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Alex1iv/Hotel-rating-prediction

Prediction of hotel ratings basing on customers feedback to prevent rating fraud.

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Alex1iv/Deposit-subscription

It was studied factors of subscription for a term deposit after the direct marketing campaign.

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DohyunBu/LG-AIMERS_03-49_AT_MEETINGROOM..._Table_No.2

2024 상반기 LG Aimers 오프라인 해커톤 대회 (최우수상)

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ahmedshahriar/Customer-Churn-Prediction

Extensive EDA of the IBM telco customer churn dataset, implemented various statistical hypotheses tests and Performed single-level Stacking Ensemble and tuned hyperparameters using Optuna.

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CRDK1009/Exploring-Planets

Algorithms used to confirm whether a celestial body is a planet or not.

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mo26-web/Induction-Motor-Faults-Detection-with-Stacking-Ensemble-Method-and-Deep-Learning

This is a induction motor faults detection project implemented with Tensorflow. We use Stacking Ensembles method (with Random Forest, Support Vector Machine, Deep Neural Network and Logistic Regression) and Machinery Fault Dataset dataset available on kaggle.

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MrTejas/ML-Algos

A collection of fundamental Machine Learning Algorithms Implemented from scratch along-with their applications for various ML tasks like clustering, thresholding, data analysis, prediction, regression and image classification.

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AbhishekGit-hash/Credit-Card-Lead-Prediction

A machine learning model to predict whether a customer will be interested to take up a credit card, based on the customer details and its relationship with the bank.

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MsTao-68/Debt-Churn-Data-Analysis

使用比赛方提供的脱敏数据，进行客户信贷流失预测。

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niveditha093/VisaApproval

Visa approval process by leveraging machine learning on OFLC's extensive dataset, aiming to recommend suitable candidate profiles for certification or denial based on crucial drivers.

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AkashBangalkar/Cancer-Diagnosis

Machine Learning - Multiclass Classification

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FernandoLpz/Stacking-Blending-Voting-Ensembles

This repository contains an example of each of the Ensemble Learning methods: Stacking, Blending, and Voting. The examples for Stacking and Blending were made from scratch, the example for Voting was using the scikit-learn utility.

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SohelRaja/Ensemble-Classifier-Model

Implementation of Ensemble Learning, Decision Tree, Random Forest, SVM, KNN, Logistic Regression, Bagging, Boosting and Stacking approach to analysis and predict the abnormal and normal behavior of Imbalanced Colon Dataset.

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NickVasenkov/CO2-Emissions

A Kaggle competition (spatial and time data, regression). A top 23% solution.

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cnai-ds/Premium-Prediction-Natural-Hazards

Prediction of market premiums for property damage and business interruption insurance products. Added natural hazard data and stacked 3 best models as the final model.

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fjpacheco/machine-learning

Trabajos prácticos realizados en la materia Organización de Datos de la FIUBA.

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vahadruya/Capstone_Regression_NYC_Taxi_Trip_Duration_Prediction

This project aims to predict the Taxi-trip duration within NYC based on several factors as predictors. Various combinations of relevant features are explored as iterations. After analysing the dataset, important and necessary features are selected. Several regression models are implemented & evaluated based on R2 & RMSE, & predictions visualised

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codiceSpaghetti/VoiceVibes

VoiceVibes presents a solution for speech emotion recognition, featuring six innovative AI model architectures designed to accurately categorize emotional expressions conveyed through speech.

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micheleandreucci/Data-Mining-2

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Yassaadi/bank_scoring

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Yassaadi/energy_ghg_prediction

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nevermorerr/Crypto-Staking-Bot

Crypto Stacking Bot

Size: 1000 Bytes - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 13 - Forks: 0

aayush301/Machine-learning-lab

This repository contains several ML algorithms wriiten from scratch that are covered in ML lab.

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avd1729/Credit-classification

Credit-classification using Stacking Classifier

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BrighentiPatrik/Model-for-predicting-student-graduation-grade

Machine Learning Model to predict student graduation grade

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adharshvenkat/loan-defaults-prediction

A Machine Learning Project that aims to perform loan defaults prediction to help banks mitigate the risk of lending bad loans

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maglili/ai_cup-movie_comment

Stacking bert model for movie sentiment analysis competition.

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rochitasundar/Customer-profiling-using-ML-EasyVisa

The aim is to find an optimal ML model (Decision Tree, Random Forest, Bagging or Boosting Classifiers with Hyper-parameter Tuning) to predict visa statuses for work visa applicants to US. This will help decrease the time spent processing applications (currently increasing at a rate of >9% annually) while formulating suitable profile of candidates more likely to have the visa certified.

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arash-mehrzadi/A-Stacking-Based-Model-for-Non-Invasive-Detection-of-Coronary-Heart-Disease

A Stacking-Based Model for Non-Invasive Detection of Coronary Heart Disease

Language: Python - Size: 8.62 MB - Last synced at: over 1 year ago - Pushed at: over 2 years ago - Stars: 4 - Forks: 0

LailaMahmoudi/HousePrices-AdvancedRegressionTechniques-DataVisualization

Kaggle Competition : Predicting house prices using a collection of advanced regression techniques and data visualization with plotly

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ds-wook/amex-default-prediction

Kaggle Competition

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OlayinkaJames01/DataFestAfrica-ML-Data-Hackathon Fork of mamakay2212/DataFestAfrica-ML-Data-Hackathon

A machine learning datathon by DataFest Africa

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Frank6496/Language-Identification-Hackathon

Language classification problem: which identifies South Africa's 11 official Languages through text data

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rdev12/Customer-Attrition-Prediction

Based on data such as general bio-data, payment history, and subscriptions, this stacking-ensemble model predicts whether a customer continues to use the service or not (attrition) with an accuracy of 83.14%

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ds-wook/ai-hackathon

🏆데이콘 AI해커톤 대회 우수상 솔루션🏆

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KelvinLam05/demand_prediction

Using machine learning methods to predict demand for bike sharing.

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maz2198/Machine-Learning

This repository represents several projects completed in IE HST's MS in Business Analytics and Big Data's Machine Learning courses

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Aryan0199/Heart-Stroke-Prediction-using-Ensemble-Learning-with-various-ML-algorithms

In this project, different supervised machine learning algorithms like Decision Tree, Naive Bayes, K-nearest neighbour,Random Forsest, Logistic Regression etc. were trained on the training data set and then Ensemble Learning was used to improve the accuracy were

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Yoojin730/DataModeling_forRightofMobility

2022-01 데이터마이닝이론및응용 프로젝트 <장애인 이동권 제고를 위한 콜택시 이용편의 증진 방안 : 서울특별시를 중심으로>

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better62/Diabetes-Prediction-Using-Stacking-Model

성균관대학교 우수학부생 연구학점제를 통해 작성한 논문입니다.

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Montanaz0r/Kaggle-House-Prices-Advanced-Regression-Techniques

Full data science project workflow that placed me in the top 5% of all competitors (0.11931).

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Pradnya1208/House-prices-prediction

Predict sales prices and practice feature engineering and advanced regression techniques.

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jeevankande/Ensemble-Techniques

Ensemble methods is a machine learning technique that combines several base models in order to produce one optimal predictive model. To better understand this definition lets take a step back into ultimate goal of machine learning and model building. This is going to make more sense as I dive into specific examples and why Ensemble methods are used.

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MafikengZ/Hackathon-Language-Identification

Language classification problem: which identifies South Africa's 11 official Languages through text data

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K1A2/dacon_credit_card

데이콘 신용카드 사용자 연체 예측 AI 경진대회 코드

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toan01-uet/sentiment

final_project of sun_ai_courses

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amit0902/Classification

Logisitc Regression - A Binary Classification Method

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somjit101/NLP-CaseStudy-Personalized-Cancer-Diagnosis

In this problem statement, a sequence of genetic mutations and clinical evidences, i.e. descriptive texts as recorded by domain experts are used to classify the mutations to conclusive categories, to be used for diagnosis of the patient.

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disha2sinha/UndErNsembled Fork of SohelRaja/UndErNsembled

In this project, we reduced an imbalanced dataset to a balanced dataset using Under-sampling approach by applying Consensus Clustering using 'Simple Majority Voting' consensus function and further saw the increase in the accuracy of disease prediction by running multiple classifiers with bagging and boosting technique.

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dhamvi01/Stacking-to-Choose-the-Best-Possible-Algorithm

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SteliosGian/Predicting-Customer-Churn

Size: 8.79 KB - Last synced at: about 2 years ago - Pushed at: about 6 years ago - Stars: 1 - Forks: 0

jeremySrgt/kaggle_walmart

Kaggle competition on Walmart data

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sujeethshetty/hackathon-projects

Project work related to various hackathons

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jddeguia/energy-output-profiling

Notebook files for classification and detection of anomalous trend in time series inverter data

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Aujasvi-Moudgil/Ensemble-Learning

Ensemble Learning Methods using Python

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