benedekrozemberczki/awesome-gradient-boosting-papers

A curated list of gradient boosting research papers with implementations.

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zygmuntz/hyperband

Tuning hyperparams fast with Hyperband

Language: Python - Size: 370 KB - Last synced at: 3 months ago - Pushed at: almost 7 years ago - Stars: 593 - Forks: 72

sharmapratik88/AIML-Projects

Projects I completed as a part of Great Learning's PGP - Artificial Intelligence and Machine Learning

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asafschers/scoruby

Ruby Scoring API for PMML

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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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KwokHing/YandexCatBoost-Python-Demo

Demo on the capability of Yandex CatBoost gradient boosting classifier on a fictitious IBM HR dataset obtained from Kaggle. Data exploration, cleaning, preprocessing and model tuning are performed on the dataset

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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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wangy8989/Bankruptcy-Prediction-using-Machine-Learning

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

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krpiyush5/Facebook-Friend-Recommendation-using-Graph-Mining

In this challenge we have given a directed social graph, and we have to predict missing links to recommend users (Link Prediction in graph)

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adamingas/ordinalgbt

A package to build Gradient boosted trees for ordinal labels

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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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dayfundora/Personality-Type

Recognition of Persomnality Types from Facebook status using Machine Learning

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Jaap-Meerhof/Federated_XGBoost_Python

FederBoost's Federated Gradient Boosting Decision Tree Algorithm, Federated enabled Membership Inference

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indrapaul824/Coronary-Heart-Disease-Prediction

This contains the Jupyter Notebook and the Dataset for the mentioned Classification Predictive Modeling Project

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DmitryAsdre/rocauc_pairwise

RocAuc Pairiwse objective for gradient boosting

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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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leffff/stackboost

Open source gradient boosting library

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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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therealAJ/buckets-plus-plus

A way to predict an NBA's players chance of making a shot using machine learning

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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.

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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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VivekSagarSingh/Probability-of-Credit-card-Default

Classification problem using multiple ML Algorithms

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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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billy-enrizky/Loan-Prediction-Status

Explore an ML model with Logistic Regression, SVM, Gradient Boosting, Random Forest, and Decision Tree, enhanced via Hyperparameter Tuning. Experience our GUI-based ML model with 82.49% accuracy. Try it now!

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PavanParchuri/Body-Fitness-Prediction

⚡ BODY FITNESS PREDICTION is a Machine Learning based web application that is used to predict the fitness levels of a person (Active/Inactive).

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HCYENDLURI/Comparing-6-Classifiers-for-Sepsis-Dataset

To Detect Sepsis Disease using six Classifiers on clinical data

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rajtulluri/Predicting-Loan-Approval

This repo contains step-by-step procedure to predict whether a customer's Loan request is Approval or rejected, Based on the compition on Analytics Vidhya

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asafschers/scorystal

Crystal Scoring API for PMML

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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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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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karthik-d/FungiCLEF-2022-using-Network-Ensembles

Scripts, figures and working notes for the participation in FungiCLEF-2022, part of the 13th CLEF Conference, 2022

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S-iddharth/NeuroNexus

This repository contains 2 ML projects for my internship under NeuroNexus Innovations.

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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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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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Prajwal10031999/Titanic-Passenger-Survival-Predictions-using-machine-learning

A machine learning model to predict the survived passengers from the titanic disaster.

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NikhilSKashyap/11-Projects-to-DataScience

In this 11 project series, we will explore Data Science concepts using different Kaggle datasets.

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HarigovindV10/Credit-Card-Fraud-Detection

A credit card fraud detection algorithm.

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mlisovyi/KaggleSantander2019

Example of MLflow usage for a kaggle competition (Santander 2019)

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vshantam/House-Prices-Advanced-Regression-Techniques

Predict sales prices and practice feature engineering, RFs, and gradient boosting

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akshaymehra24/who-is-more-influential

Given activity of 2 users on Twitter, predict who is more influential among them

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KKeshav1101/mini_project

A Django Application Interface for Hate Speech Detection Mini Project

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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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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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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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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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MAHMOUD2ABDALLAH/family-members-segmentation

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

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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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alloverheada2/Gradient-Full

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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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aNdr3W03/Employee-Attrition-Problem

Employee Attrition Problem Analysis and Prediction

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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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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.

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

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

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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amir-rs/Brest-Cancer-Prediction-using-ML

Language: Jupyter Notebook - Size: 2.56 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 1 - Forks: 1

DandiMahendris/Auto-Insurance-Fraud-Detection

This research goal is to build binary classifier model which are able to separate fraud transactions from non-fraud transactions.

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SunilGolden/Kaggle-ICR

ICR - Identifying Age-Related Conditions.

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karthik-d/SnakeCLEF-2022-using-Network-Ensembles

Scripts, figures and working notes for the participation in SnakeCLEF-2022, part of the 13th CLEF Conference, 2022

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gb-pignatti/ML_from_scratch

I code from scratch various Machine Learning algorithms.

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luuisotorres/Credit-Card-Fraud-Detection

For this project, I used four different classification algorithms to detect fraudulent credit card transactions.

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6shun/mbti-classifier

CS289A | Supervised ML on MBTI types

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mrinalmayank7/machine_learning_models

This repository consist of various machine learning models along with the dataset. The models are trained with widely used ML algorithms like Gradient Boost , Random Forest etc. Pickle is used to serialize ML algorithms for predictions or availing it for the server use.

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JJBarata/ml_anomaly_detection

Modelo preditivo, baseado em 6 modelos de classificação binária e multiclasse, capaz de distinguir entre conexões "ruins", que são os ataques, das conexões "boas" ou normais.

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Pradnya1208/Loan-approval-prediction

It is a classification Problem where we are supposed to predict whether a loan would be approved or not.

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jialincheoh/finding-donors

Finding Donors with Machine Learning ( Support Vector Machine, Gradient Boosting Classifier, Random Forest Classifier )

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ryanquinnnelson/CMU-02750-Study-of-Type-2-Active-Learning-Algorithms

Spring 2021 - Automation of Scientific Research - course project

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Zauverer/Test-TSA-Models

Twitter Sentiment Analisys, comparing different models

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sermonzagoto/Customer_Churn_Prediction

Customer Churn Prediction using Machine Learning

Language: Jupyter Notebook - Size: 472 KB - Last synced at: 3 months ago - Pushed at: almost 5 years ago - Stars: 1 - Forks: 3

rajtulluri/Employee-Promotion-Prediction

This repo contains step by step procedure to predict whether an employee is promoted or not. Based on the Practice competition on AnalyticsVidhya

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LeondraJames/Private_Public_Colleges

Predicting whether a university is private or public using tree based models (ie: decision tree classifier, random forest classifier and gradient boosted tree classifier) using PySpark and Databricks.

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

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

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Faiyadnub/Spaceship-Titanic

Spaceship Titanic project.

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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

Language: Python - Size: 22.5 KB - Last synced at: 13 days ago - Pushed at: 13 days ago - Stars: 0 - Forks: 0

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

Language: Jupyter Notebook - Size: 6.1 MB - Last synced at: 19 days ago - Pushed at: 19 days ago - Stars: 0 - Forks: 0

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.

Language: Jupyter Notebook - Size: 811 KB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 0 - Forks: 0

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.

Language: Jupyter Notebook - Size: 913 KB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 0 - Forks: 0

Parnika798/Customer-Segmentation

Customer Behaviour Analysis and Churn Predictor

Language: Python - Size: 183 KB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0

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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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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hdangle31/DS-Machine-Learning-Flights-2022

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

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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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djdhairya/Liver-Disease-Classification

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Riciokzz/Spaceship-Titanic

Spaceship Titanic project.

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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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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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anushkundu/Churn-Prediction

Telecom Customer Churn Prediction Using Machine Learning!

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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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bennettbDEV/GradientBoostingv2

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

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

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

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