GitHub topics: gradient-boosting-classifier

Faiyadnub/Spaceship-Titanic

Spaceship Titanic project.

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benedekrozemberczki/awesome-gradient-boosting-papers

A curated list of gradient boosting research papers with implementations.

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JSalazarAlt/qot-predictions

A machine learning project implementing Quality of Transmission (QoT) prediction in optical networks using Gradient Boosting algorithms for SNR estimation and Modulation Format assignment.

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alexandramahajan/Starship-Pointer

🚀 A machine learning co-pilot for your next planetary adventure. Predicts exoplanet types using gradient-boosted trees trained on NASA’s Exoplanet Archive with 95% accuracy.

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adamingas/ordinalgbt

A package to build Gradient boosted trees for ordinal labels

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mehrdadhz-77/us-visa-prediction

A Machine Learning pipeline that analyzes U.S. working visa application data to predict case certification outcomes, helping employers and applicants understand key factors influencing approvals

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Aravindmax/Employee-salary-prediction

This Employee salary prediction uses GradientBoostingClassifier machine learning algorithm to predict the classified predictions which will be above 50000rs or below.

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jigyasaG18/Employee-Salary-Prediction-Jigyasa

PayNexus is a machine learning-powered web app that predicts employee salaries based on role, education, and experience. Built using Python, Streamlit, and scikit-learn, it supports both single and batch predictions. The app includes advanced features like resume parsing via NLP and interactive visual analytics. Ideal for job seekers, HR profession

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Parnika798/Customer-Segmentation

Customer Behaviour Analysis and Churn Predictor

Language: Python - Size: 896 KB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 0 - Forks: 0

Kumpatlapavankumar/Medical-Insurance-Cost-Estimation-Using-Machine-Learning

Using python,numpy,pandas,seaborn,matplotlib and machine learning techniques

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Ashis-Mishra07/Medical_Diagnose

Gain a complete and accurate understanding of the disease you’re dealing with.

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El-Bahnasawi/Analyzing-U.S.-Crime-Data

Analyze & visualize U.S. crime data + advanced ML to predict 3-year recidivism risk.

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Pratyaksh-Saxena018/Credit_Card_Approval_Project

A project made with a vision to come up with a system in order to ease-out the prediction in the credit card approval process.

Language: Python - Size: 109 MB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0

abdullahsaka/Capital_One-Data_Challenge

Data Science Challenge

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DevaYadhala-04/weather-prediction-project

Weather Prediction using Time Series Analysis

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ZionC27/MLB-Game-Winner-Predictor

MLB Game Winner Predictor using Machine Learning

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afairless/binary_classification_shap

Run histogram-based gradient boosted trees binary classifier on generated data and interpret results with standard metrics, SHAP, and supervised clustering

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Snigdho8869/Multiclass-Text-Classification

Natural Language Processing for Multiclass Classification: A repository containing NLP techniques for multiclass classification of text data.

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ShwetaPardhi0/Project-Bankruptcy_Prediction

Using various machine learning models (Logistic Regression, Gaussian Naïve Bayes, KNN, Gradient Boosting Classifier, Decision Tree Classifier, Random Forest Classifier.) to predict whether a company will go bankrupt in the following years, based on financial attributes of the company; Addressed the issue of imbalanced classes, different importance

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KKeshav1101/mini_project

A Django Application Interface for Hate Speech Detection Mini Project

Language: Python - Size: 334 KB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 1 - Forks: 1

thierrymoudiki/unifiedbooster

Unified interface for Gradient Boosted Decision Trees

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kapilsinghnegi/Fake-News-Detection

This project detects whether a news is fake or not using machine learning.

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zhull1988/Telecom-Customer-Churn-Analysis

Exploratory data analysis of telecom customer churn using Python. Includes data cleaning, visualization, and statistical tests to understand churn behavior.

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Rfldmr/smare.ai-smart-automation-report

SMARE AI is an AI-based automatic report generation system for water quality testing certification. Supported by the Gradient Booster algorithm, SMARE AI can predict water quality categories with test result data inputted by users and automatically generate test certificate reports in PDF format.

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mahnoorsheikh16/NLP-Approach-to-AI-Text-Classification Fork of andrew-jxhn/STT811_StatsProject

A text‐classification pipeline for identifying human‐ versus AI-generated responses using engineered linguistic/semantic features and PCA-reduced vectors; achieves ~85% accuracy with Logistic Regression, SVM, and MLP, and includes a fine-tuned bert-base-uncased model.

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turgunbaevaa/machineLearningProject

A complete ML project that explores feature engineering, model training (Decision Tree, Random Forest, Gradient Boosting), and model interpretation using SHAP and LIME.

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Mattytomo365/Weekly-Sales-Machine-Learning-Models

This project contributed towards my AI and Machine Learning module at university, it predicts weekly sales for retail stores using machine learning models. It includes data preprocessing, feature engineering, and training/testing of models such as Random Forest and Gradient Boosting Regressors.

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NandaKishoreReddyGajjala/Credit-Card-Fraud-Detection-with-Machine-Learning

Dataset: https://drive.google.com/file/d/1blQ8F4gLVrez-9D9Jx320vafZexEFlSN/view?usp=drive_link

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syeda434am/Suicide-Ideation-Detection

This repository aims to address the critical issue of identifying and understanding suicide ideation in social media conversations, specifically focusing on Twitter data.

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somjit101/Human-Activity-Recognition

This project is to build a model that predicts the human activities such as Walking, Walking Upstairs, Walking Downstairs, Sitting, Standing or Laying using readings from the sensors on a smartphone carried by the user.

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MUHAMMADAKMAL137/Optuna-based-Hyperparameter-Optimization-for-Machine-Learning-Models-Static-and-Dynamic-Tuning

This Optuna-based hyperparameter optimization study performs both static and dynamic tuning of hyperparameters for machine learning models (SVM, RandomForest, and GradientBoosting) to maximize accuracy. It tracks and analyzes model performance, displays the best trial results, and compares the average performance of each classifier.

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razamehar/Predicting-Bank-Customer-Churn

This project aims to predict bank customer churn using a dataset derived from the Bank Customer Churn Prediction dataset available on Kaggle. The dataset for this competition has been generated from a deep learning model trained on the original dataset, with feature distributions being similar but not identical to the original data.

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Agnij-Moitra/MSBoost

MSBoost is a gradient boosting algorithm that improves performance by selecting the best model from multiple parallel-trained models for each layer, excelling in small and noisy datasets.

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sushant1827/Machine-Learning-for-Predictive-Maintenance

Demonstrate the application of machine learning on a real-world predictive maintenance dataset, using measurements from actual industrial equipment.

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hdangle31/DS-Machine-Learning-Flights-2022

Predict Flight Cancellation Using Random Forest, XGBoost, Logistic Regression and Naive Bayes

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georgegkol/Macro-based-Asset-Allocation

This repository contains code to cluster and predict ETF returns and construct a minimum variance portfolio from a selection of bullish ETFs

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anushrey10/Fuel_Efficiency_Predictor

Welcome to the Fuel Efficiency Predictor! This advanced tool uses machine learning to predict your vehicle's fuel efficiency based on various characteristics.

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mazerunner1001/Breast-Cancer-Diagnosis-from-Thermal-Images

genetic algorithms and machine learning techniques to diagnose breast cancer from thermal images by distinguishing between cancer-positive and healthy cases.

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zygmuntz/hyperband

Tuning hyperparams fast with Hyperband

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djdhairya/Liver-Disease-Classification

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Riciokzz/Spaceship-Titanic

Spaceship Titanic project.

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asafschers/scoruby

Ruby Scoring API for PMML

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Tolumie/Ai-Machine-Learning-Projects

A collection of hands-on Artificial Intelligence (AI) and Machine Learning (ML) projects covering supervised and unsupervised learning, ensemble methods, deep learning, and model evaluation. This repository provides practical implementations using real-world datasets, making it ideal for both beginners and experienced data scientists.

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Ananyajain2004/Fake-news-detection

A python project for detecting fake news using machine learning algorithms.

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styan606/PredictingPresentationRatings_Sendsteps

How do linear and non-linear predictive models perform in predicting the quality ratings of AI-generated presentations, and which features contribute most significantly to these predictions?

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gustavoeso/PhishingURL-predictive-model

Projeto de Machine learning para desenvolver um modelo preditivo de busca de email que potencialmente seja phishing. Esse projeto foi desenvolvido no DataBricks, utilizando cluster voltado a MachineLearning.

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astroarth/AI_use_cases

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MAHMOUD2ABDALLAH/family-members-segmentation

Machine learning Classification for Family Determination for various generations by their age, height, weight, etc...

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VivekSagarSingh/Probability-of-Credit-card-Default

Classification problem using multiple ML Algorithms

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AmirHosseinSoleymani/Pred-Developer-Salary-With-GBR-model-

This project aims to predict the salary of developers using the Stack Overflow Developer Survey 2022 dataset. The prediction model is built using the Gradient Boosting Regressor (GBR) algorithm.

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anushkundu/Churn-Prediction

Telecom Customer Churn Prediction Using Machine Learning!

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ArnabKumarRoy02/Phishing-attack-detection

This project is our submission for the Kavach Hackathon 2023, in which we have created a browser extension that detects the links present in the email and classifies whether they are safe or not.

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sushant1827/Human-Activity-Recognition-with-Smartphones

Kaggle Machine Learning Competition Project : To classify activities into one of the six activities performed by individuals by reading the inertial sensors data collected using Smartphone.

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Mqtth3w/AI-unipr

Project for AI. Model to check password security with five classes: "Too weak", "Weak", "Moderate", "Strong", "Very strong". Developed in 2024 with @SasyXk

Language: Python - Size: 14 MB - Last synced at: 3 months ago - Pushed at: 9 months ago - Stars: 0 - Forks: 0

FrienDotJava/adult-census-income

A machine learning project classifying whether someone has income >$50K or <$50K using several models.

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BeheshteSadeghi/ChurnModelling

This project aims to train the best model for predicting customer churn. In this project; first, data is studied and several diagrams are depicted for storytelling. Since we face with unbalanced data, categorical data, outliers, unscaled data and ecxess of features, related packages from python is utilized to prepare data for modelling.

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BeheshteSadeghi/TitanicSurvivalPrediction_PycaretPipelineGridSearchCV

The focus of this project is on Data Cleaning, Data Analysis, Gaining an insight from Pycaret Classification tool over best ML algorithms, hyperparameter tuning through GridSearchCV for top ML algorithms and generating Pipeline for the best algorithm.

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shubhamjai9/Emotion-Based-Counsellor-Bot

An Artificial Intelligence based Chat Bot using python tools like Numpy, Pandas, Spacy etc. Counsellor Bot will mimic the characteristics and emotion interpretation skills of human and generate response on basis of emotion of engager.

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bennettbDEV/GradientBoostingv2

Information and implementation of Gradient Boosting, a flexible and performant Machine Learning technique

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alloverheada2/Gradient-Full

Size: 2.93 KB - Last synced at: 8 months ago - Pushed at: 8 months ago - Stars: 1 - Forks: 0

reillyc421/Predict-Post-shelter-Outcomes-for-Dogs

Use classification models to predict post-shelter outcomes for dogs (adoption, euthanasia, rescue)

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Rupsvarshney/heart-disease-prediction

Machine Learning helps in predicting the Heart diseases, and the predictions made are quite accurate.

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meAnubhav/Kidney-Disease-Prediction-Model

A machine learning application, deployed using Flask, is designed to identify the presence of kidney disease in patients by analyzing various medical features.

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wlouer/HCR_000002_Parkinsons

Parkinson's Disease Diagnosis Prediction using an evaluation of classification algorithms.

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wlouer/HCR000001_BreastCancer

Exploratory Data Analysis and selection of a Classification Algorithm to predict a Breast Cancer Diagnosis

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aNdr3W03/Employee-Attrition-Problem

Employee Attrition Problem Analysis and Prediction

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rockett-m/JPMC-Quant-Research

JPMorgan Quant Research program

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vignesh4005/Crowdfunding_Campaign_Success_Prediction

This project aims to predict the success of crowdfunding campaigns using machine learning models: Ensemble Learning, Naive Bayes, and Support Vector Machine (SVM).

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wangy8989/Bankruptcy-Prediction-using-Machine-Learning

Using various machine learning models to predict whether a company will go bankrupt

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ergineeer/HeartAttackPrediction

Heart Attack Prediction Study - Python & MATLAB

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harmanveer-2546/Diabetes-Prediction-Using-Machine-Learning

Diabetes is a medical disorder that affects how the body uses food for energy. When blood sugar levels rise, the pancreas releases insulin. If diabetes is not managed, blood sugar levels can rise, increasing the risk of heart attack and stroke. We used Python machine learning to forecast diabetes.

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phalconVee/telco-churn-ai-ml

Predictive models to analyse a telco firm's customer-level data, to identify customers at high risk of churn and identify the leading indicators.

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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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emma-horton/Leveraging-Machine-Learning-to-Predict-Liver-Cirrhosis-Outcomes-from-Clinical-Data

Predicting liver cirrhosis outcomes using machine learning models based on clinical data.

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kapasitejas/Telecom_Churn_Case_Study

To predict if a customer will churn, given the ~170 columns containing customer behavior, usage patterns, payment patterns, and other features that might be relevant. Your target variable is "churn_probability"

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FYT3RP4TIL/Fake-News-Detection-V4-Gensim-GoogleNews300

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FYT3RP4TIL/NewsClassify-V2-Spacy-WordEmbeddings

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shwetapardhi/Project-Bankruptcy_Prediction

Using various machine learning models (Logistic Regression, Gaussian Naïve Bayes, KNN, Gradient Boosting Classifier, Decision Tree Classifier, Random Forest Classifier.) to predict whether a company will go bankrupt in the following years, based on financial attributes of the company; Addressed the issue of imbalanced classes, different importance

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filsan-musa/Project-Twitter_Bot_Detection

Using a synthetic dataset from Kaggle, generated with Python's Faker library to mimic real Twitter data, we train several classical machine learning models (ie. classical classification algorithms, as well as ensemble methods)to identify bots from real users.

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CarbezonKARDE/Heart-Attack-Analysis-and-Prediction

A small demonstration of my knowledge of machine learning algorithms.

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Ehtisham33/Diabetes-Prediction

This project aims to predict whether a person has diabetes or not using key health metrics such as glucose levels and BMI. The project involves data preprocessing, feature selection, model training, evaluation, and prediction using various machine learning algorithms.

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leabrodyheine/Water-Pump-Status-Prediction

This project implements machine learning models to predict the status of water pumps in Tanzania using data from DrivenData's competition. The project includes preprocessing steps, model evaluation using cross-validation, and hyperparameter optimization with Optuna.

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tboudart/Life-Expectancy-Regression-Analysis-and-Classification

I contributed to a group project using the Life Expectancy (WHO) dataset from Kaggle where I performed regression analysis to predict life expectancy and classification to classify countries as developed or developing. The project was completed in Python using the pandas, Matplotlib, NumPy, seaborn, scikit-learn, and statsmodels libraries. The regression models were fitted on the entire dataset, along with subsets for developed and developing countries. I tested ordinary least squares, lasso, ridge, and random forest regression models. Random forest regression performed the best on all three datasets and did not overfit the training set. The testing set R2 was .96 for the entire dataset and developing country subset. The developed country subset achieved an R2 of .8. I tested seven different classification algorithms to classify a country as developing or developed. The models obtained testing set balanced accuracies ranging from 86% - 99%. From best to worst, the models included gradient boosting, random forest, Adaptive Boosting (AdaBoost), decision tree, k-nearest neighbors, support-vector machines, and naive Bayes. I tuned all the models' hyperparameters. None of the models overfitted the training set.

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Sachinthotre/Credit_Card_Fraud_Detection

Utilizing machine learning models including logistic regression, random forest, gradient boosting, and neural networks to identify fraudulent credit card transactions. Dataset, consisting of PCA-transformed features and unbalanced classes, required precision-recall metrics for accurate evaluation. Developed in Python using TensorFlow and scikit.

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prajwalp3/Cardiovascular-Disease-prediction-using-Machine-learning-models

Our project utilizes machine learning models to predict cardiovascular diseases (CVDs) by analyzing diverse datasets and exploring 14 different algorithms. The aim is to enable early detection, personalized interventions, and improved healthcare outcomes.

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Ezgigunbatar/FertilityStudy

This is a master thesis project done by Ezgi Günbatar for Applied Data Science program at Utrecht University. The repository contains datasets and codebooks which are used in "The Role of Social Networks and Personal Characteristics in Shaping Fertility Intentions: A Multi-Method Machine Learning Perspective" study.

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hugohiraoka/Travel_Package_Purchase_Prediction

Model to Predict if a customer will purchase a Travel Package

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sanhiitaa/fastag-fraud-detection-classification

Fastag Fraud Detection Classification System

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sayadennis/classical-ml

Simple and flexible classical ML module that can be used for recording baseline ML performance.

Language: Python - Size: 78.1 KB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0

SophiaRazzaq/Landslide-Insights-and-Prediction

Machine Learning

Language: Jupyter Notebook - Size: 15.4 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0

MohamedKhalidLx/Loan-Eligibility-Prediction-Web-App

Loan Eligibility Prediction Model: A machine learning application to predict loan approval based on applicant data. Includes a web interface for submitting loan applications and receiving predictions. Built with Python and Jupyter Notebook.

Language: Jupyter Notebook - Size: 681 KB - Last synced at: 6 months ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0

NishraMahveen/A-Robust-Approach-for-Effective-Spam-Detection-using-Supervised-Learning-Technique

This project detects spam messages in SMS, including those written in regional languages typed in English. It uses an extended SMS dataset and applies the Monte Carlo method with various supervised learning algorithms to improve spam detection.

Language: HTML - Size: 170 KB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0

MatteoLucas/Rakuten_Data_Challenge

Ce projet est une proposition de solution au Rakuten Data Challenge. L'objectif est de mettre en œuvre différentes méthodes de Machine Learning et Deep Learning pour résoudre le problème.

Language: Python - Size: 2.77 GB - Last synced at: 10 months ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0

VibolvatanakPOCH/Telecom-Customer-Churn-Analysis-Prediction

Telecom Customer Churn Analysis & Prediction project uses Gradient Boosting for precise predictions, Power BI for churn pattern visualizations, and Streamlit for interactive insights. With robust code and meticulous data preprocessing, stakeholders access accurate predictions to optimize retention and drive profitability.

Language: Jupyter Notebook - Size: 11 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 4 - Forks: 1

astonglen/Employee-Attrition

This project analyzes employee attrition data to uncover key factors, predict turnover, and develop strategies for retention, ultimately enhancing organizational stability and performance.

Language: Jupyter Notebook - Size: 1.68 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 1 - Forks: 0

roniantoniius/American-Company-Bankrupt-Prediction-Using-Neural-Network

Language: Jupyter Notebook - Size: 16.8 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 1 - Forks: 0

sayande01/Fake_News_Prediction_Machine_Learning

This project evaluates logistic regression, random forest, decision tree, and gradient boosting classifier models for fake news detection. Using labeled data, it analyzes accuracy, confusion matrices, and ROC curves to understand each model's effectiveness in discerning between real and fake news.

Language: Jupyter Notebook - Size: 819 KB - Last synced at: about 1 month ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0