xgboost-algorithm | Topic | Ecosyste.ms: Repos

Topic: "xgboost-algorithm"

susanli2016/Machine-Learning-with-Python

Python code for common Machine Learning Algorithms

Language: Jupyter Notebook - Size: 58 MB - Last synced at: 24 days ago - Pushed at: about 1 year ago - Stars: 4,417 - Forks: 4,820

benedekrozemberczki/awesome-gradient-boosting-papers

A curated list of gradient boosting research papers with implementations.

Language: Python - Size: 1.48 MB - Last synced at: 4 days ago - Pushed at: about 1 year ago - Stars: 1,022 - Forks: 160

chasedehan/BoostARoota

A fast xgboost feature selection algorithm

Language: Python - Size: 693 KB - Last synced at: about 1 month ago - Pushed at: about 4 years ago - Stars: 221 - Forks: 38

ldv1/LinXGBoost

Extension of the awesome XGBoost to linear models at the leaves

Language: Python - Size: 5.42 MB - Last synced at: over 1 year ago - Pushed at: almost 6 years ago - Stars: 73 - Forks: 19

jinlow/forust

A lightweight gradient boosted decision tree package.

Language: Rust - Size: 13.4 MB - Last synced at: 17 days ago - Pushed at: 17 days ago - Stars: 70 - Forks: 7

KSpiliop/Fraud_Detection

Tuning XGBoost hyper-parameters with Simulated Annealing

Language: Jupyter Notebook - Size: 463 KB - Last synced at: about 2 years ago - Pushed at: about 8 years ago - Stars: 44 - Forks: 14

sauravmishra1710/Heart-Failure-Condition-And-Survival-Analysis

Perform a survival analysis based on the time-to-event (death event) for the subjects. Compare machine learning models to assess the likelihood of a death by heart failure condition. This can be used to help hospitals in assessing the severity of patients with cardiovascular diseases and heart failure condition.

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farhanchoudhary/Machine_Learning_A-Z_All_Codes_and_Templates

All codes, both created and optimized for best results from the SuperDataScience Course

Language: Python - Size: 5.7 MB - Last synced at: almost 2 years ago - Pushed at: over 7 years ago - Stars: 31 - Forks: 32

RudreshVeerkhare/CustomXGBoost

Modified XGBoost implementation from scratch with Numpy using Adam and RSMProp optimizers.

Language: Jupyter Notebook - Size: 57.6 KB - Last synced at: 24 days ago - Pushed at: almost 5 years ago - Stars: 26 - Forks: 9

vaishnavipatil29/Career-Guidance-ML-Project

Career Guidance System Using Machine Learning Techniques

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yogeshwaran-shanmuganathan/Airline-Passenger-Satisfaction

Determining the important factors that influences the customer or passenger satisfaction of an airlines using CRISP-DM methodology in Python and RapidMiner.

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sohammanjrekar/Multiple-Disease-Prediction-Webapp

Designed web app employs the Streamlit Python library for frontend design and communicates with backend ML models to predict the probability of diseases. It's capable of predicting whether someone has Diabetes, Heart issues, Parkinson's, Liver conditions, Hepatitis, Jaundice, and more based on the provided symptoms, medical history, and results.

Language: Python - Size: 79.9 MB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 21 - Forks: 7

pankajrawat9075/fantasy-sports-prediction

We have used our skill of machine learning along with our passion for cricket to predict the performance of players in the upcoming matches using ML Algorithms like random-forest and XG Boost

Language: Python - Size: 7.49 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 19 - Forks: 10

eswar3/Zillow-prediction-models

Machine Learning Project using Kaggle dataset

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ojasphansekar/Zillow-Home-Value-Prediction

XGBoost, LightGBM, LSTM, Linear Regression, Exploratory Data Analysis

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MoinDalvs/Gradient_Boosting_Algorithms_From_Scratch

4 Boosting Algorithms You Should Know – GBM, XGBoost, LightGBM & CatBoost

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tanishq-ctrl/House-price-prediction-and-visualization

This repository contains code and data for analyzing real estate trends, predicting house prices, estimating time on the market, and building an interactive dashboard for visualization. It is structured to cater to data scientists, real estate analysts, and developers looking to understand property market dynamics.

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KrishArul26/Air-Quality-Index-prediction_with_deployment

India is one of the countries with the highest air pollution country. Generally, air pollution is assessed by PM value or air quality index value. For my further analysis, I have selected PM-2.5 value to determine the air quality prediction and the India-Bangalore region. Also, the data was collected through web scraping with the help of Beautiful Soup.

Language: Jupyter Notebook - Size: 17 MB - Last synced at: 22 days ago - Pushed at: about 1 year ago - Stars: 8 - Forks: 2

omarmhaimdat/xgboost_student_performance

Introduction to XGBoost with an Implementation in an iOS Application

Language: Swift - Size: 1.5 MB - Last synced at: about 1 year ago - Pushed at: almost 2 years ago - Stars: 8 - Forks: 1

leonardodepaula/xgbimputer

Extreme Gradient Boost imputer for Machine Learning.

Language: Python - Size: 120 KB - Last synced at: 24 days ago - Pushed at: about 3 years ago - Stars: 8 - Forks: 1

Mohsinrazaa/All-Machine-Learning-Algorithm

Machine Learning Assignments of inuroun academy ML with master deployment and deep learning 29th Aug. 2020

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kush1912/FAKE-NEWS-DETECTION

Machine learning Based Minor Project, which uses various classification Algorithms to classify the news into FAKE/REAL, on the basis of their Title and Body-Content. Data has been collected from 3 different sources and uses algorithms like Random Forest, SVM, Wordtovec and Logistic Regression. It gave 94% accuracy.

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MitchellTesla/Max-Q Fork of arXiv-research/Quatm

Machine-Learning: eXtreme Gradient-Boosting Algorithm Stress Testing

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IshtyM/Shipping-Pricing-Prediction

Predicting the supply chain shipment pricing based on the available factors in the dataset using the classical machine learning algorithms.

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rajatbansal01/Machine_Learning-and-Data_Analysis

This repository contains various machine problems with solutions with various algorithms.

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omerfarukeker/The-Complete-Journey

The Complete Journey Dataset: Churn Prediction

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rishanki/Xgboost-VS-Catboost-Vs-LiteGBM

The python notebook is on googles new collabatory tool. Its a churn model being run on 3 different algorithms to compare.

Language: Jupyter Notebook - Size: 294 KB - Last synced at: about 2 years ago - Pushed at: about 7 years ago - Stars: 7 - Forks: 9

susanli2016/Machine-Learning-with-R

R codes for common Machine Learning Algorithms

Language: R - Size: 0 Bytes - Last synced at: 29 days ago - Pushed at: almost 8 years ago - Stars: 7 - Forks: 6

haroldeustaquio/Machine-Learning-Projects

This repository contains Machine Learning mini-projects focused on different predictive models, from linear regression to more advanced techniques. It also includes more comprehensive end-to-end projects covering the entire ML workflow, from data preparation to model deployment.

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datacrypto-analytics/crypto-analysis-cli

Analise todas as criptomoedas disponíveis na binance spot com algoritmos Machine Learning.

Language: Python - Size: 1.65 MB - Last synced at: 22 days ago - Pushed at: over 4 years ago - Stars: 5 - Forks: 2

a3X3k/Spam-Email-Detection

Size: 67.9 MB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 4 - Forks: 0

IshtyM/Prediction-of-Shows-and-No-Shows-in-HealthCare-Industry

To predict whether booked appointment will be completed or it will be no show.

Language: Python - Size: 72.3 KB - Last synced at: over 1 year ago - Pushed at: over 3 years ago - Stars: 4 - Forks: 1

NamrataThakur/Airbnb-New-User-Prediction

The problem that this case study is dealing with predicts the location that a user is most likely to book for the first time. The accurate prediction helps to decrease the average time required to book by sharing more personalized recommendations and also in better forecasting of the demand. We use the browser’s session data as well as the user’s demographic information that is provided to us to create features that help in solving the problem.

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TanerArslan/Benchmarking_Classifiers_after_SVM-RFE

Evaluating multiple classifiers after SVM-RFE (Support Vector Machine-Recursive Feature Elimination)

Language: Python - Size: 22.5 KB - Last synced at: about 2 years ago - Pushed at: about 4 years ago - Stars: 4 - Forks: 1

abhilash1910/NLP-Workshop-ML-India

NLP Workshop -ML India

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ankit-kothari/Credit-Risk-Analysis

Predicting the ability of a borrower to pay back the loan through Traditional Machine Learning Models and comparing to Ensembling Methods

Language: Jupyter Notebook - Size: 768 KB - Last synced at: about 2 years ago - Pushed at: over 4 years ago - Stars: 4 - Forks: 4

govardhan26/Parkinsons-Disease-Prediction

As an early diagnosis step machine learning classifiaction algorithms could be used in finding if the patient is prone to parkinsons disease.

Language: Jupyter Notebook - Size: 266 KB - Last synced at: about 2 years ago - Pushed at: over 5 years ago - Stars: 4 - Forks: 2

mieskolainen/icenet

D<ee>p Learning [dev library]

Language: Python - Size: 27.1 MB - Last synced at: 6 months ago - Pushed at: 6 months ago - Stars: 3 - Forks: 6

josedv82/NBA_Schedule_XGBoost_Classifier

Predicting NBA game outcomes using schedule related information. This is an example of supervised learning where a xgboost model was trained with 20 seasons worth of NBA games and uses SHAP values for model explainability.

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g-aditi/customer-personality-analysis

Using a Kaggle dataset, customer personality was analysed on the basis of their spending habits, income, education, and family size. K-Means, XGBoost, and SHAP Analysis were performed.

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IshtyM/Kidney-Disease-Analysis

Machine learning algorithm is used to detect whether the person will suffer from chronic kidney disease or not.

Language: Jupyter Notebook - Size: 406 KB - Last synced at: over 1 year ago - Pushed at: almost 4 years ago - Stars: 3 - Forks: 2

sakusuma/CreditCardFraudDetection

Although digital transactions in India registered a 51% growth in 2018-19, their safety remains a concern. Fraudulent activities have increased severalfold, with around 52,304 cases of credit/debit card fraud reported in FY'19 alone. Due to this steep increase in banking frauds, it is the need of the hour to detect these fraudulent transactions in time in order to help consumers as well as banks, who are losing their credit worth each day. Machine learning can play a vital role in detecting fraudulent transactions. Imagine you get a call from your bank, and the customer care executive informs you that your card is about to expire in a week. Immediately, you check your card details and realise that it will expire in the next 8 days. Now, in order to renew your membership, the executive asks you to verify a few details such as your credit card number, the expiry date and the CVV number. Will you share these details with the executive? In such situations, you need to be careful because the details that you might share with them could grant them unhindered access to your credit card account.The aim of this project is to predict fraudulent credit card transactions using machine learning models. The data set that you will be working on during this project was obtained from Kaggle. It contains thousands of individual transactions that took place over a course of two days and their respective labels.

Language: Jupyter Notebook - Size: 841 KB - Last synced at: about 2 years ago - Pushed at: over 4 years ago - Stars: 3 - Forks: 0

josephpcowell/cowell_proj_3

Metis Project 3: Supervised Machine Learning with a Categorical Target (predicting credit card fraud)

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prashanthm07/Twitter_Sentiment_Analysis-Using-ML-and-NLP

The objective of this project is to detect hate speech in tweets. For the sake of simplicity, we say a tweet contains hate speech if it has a racist or sexist sentiment associated with it. So, the task is to classify racist or sexist tweets from other tweets.

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yashkim77/AV_Club_Mahindra_DataOlympics_ML_Hackathon

Club Mahindra Data Olympics

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sid321axn/housing_price_prediction_king_county_USA

In this project, I have predicted Housing sales price prices for King County,USA which includes Seattle. It includes homes sold between May 2014 and May 2015. It has 19 house features plus the price and the id columns, along with 21613 observations. In this project I have done the implementation of different Boosting regression machine learning models such as Gradient Boosting, eXtreme Gradient Boosting (XGB) and Adaboost. In this project, I have also used Permutation Importance for filtering the irrelevant features of the dataset. In this project, I have predicted Housing sales price prices for King County,USA which includes Seattle. It includes homes sold between May 2014 and May 2015. It has 19 house features plus the price and the id columns, along with 21613 observations. In this project I have done the implementation of different Boosting regression machine learning models such as Gradient Boosting, eXtreme Gradient Boosting (XGB) and Adaboost. In this project, I have also used Permutation Importance for filtering the irrelevant features of the dataset. Maximum Accuracy achieved around 98.59%.

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Tez1s/walmart_xgb_cv

Walmart Weekly Sales Forecasting Using XGB and Cross Validation 🚀

Language: Jupyter Notebook - Size: 288 KB - Last synced at: 23 days ago - Pushed at: 23 days ago - Stars: 2 - Forks: 0

jay37749/Ultimate-Crypto-Trading-Bot

Welcome to the Ultimate Crypto Trading Bot! This bot is designed to automate cryptocurrency trading using a hybrid strategy that combines XGBoost (machine learning) and PPO (reinforcement learning). It supports live trading, backtesting, and periodic retraining of models.

Language: Python - Size: 1.45 MB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 2 - Forks: 0

MaklonFR/PredictiveAnalytics-StudentsPerformance

Submission Dicoding Indonesia - Machine Learning Terapan (Predictive Students Analytics)

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Pratik94229/APS-Fault-Detection

In this project, the system in focus is the Air Pressure system (APS) which generates pressurized air that are utilized in various functions in a truck, such as braking and gear changes. The datasets positive class corresponds to component failures for a specific component of the APS system.

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ernestocl/Proyecto-Regresion-Machine-Learning-pricing-viajes-tren

Se pide completar el flujo completo de Regresión ML para entrenar un modelo de pricing de viajes de tren.

Language: Jupyter Notebook - Size: 8.96 MB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 2 - Forks: 0

tstran155/Time-series-regression-of-Rossmann-stores-sales-data

In this notebook, I built machine learning and neural network models to regress and predict Rossmann stores' daily sales.

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tokakhaled/Instacart-Market-Basket-Analysis

Recommender system that predicts your next order based on your previous purchases. Also, it discuss the association between product purchases.

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EnkiDoctor/The_TMDB_data_analysis

The analysis and prediction of TMDB dataset

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sonu275981/Big-Mart-Sales-Prediction

Using Machine Learning Algorithms for Regression Analysis to predict the sales pattern and Using Data Analysis and Data Visualizations to Support it.

Language: Jupyter Notebook - Size: 339 KB - Last synced at: 28 days ago - Pushed at: over 3 years ago - Stars: 2 - Forks: 3

dileepkorade/Machine-Learning_Projects

Projects based on Machine Leaning

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etendra2501/Breast-Cancer-Prediction

Extracted features of Breast cancer patient cells and normal person cells and using machine learning predict benign and Malignant Tumor.

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marcosvppfernandes/chicagoteam_quanggang

Prediction of severity of Car Crashes using Machine Learning

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arijitiiest/Malaria-Detection

Malaria Detection Project on Malaria Cells

Language: Jupyter Notebook - Size: 738 KB - Last synced at: about 2 years ago - Pushed at: almost 5 years ago - Stars: 2 - Forks: 4

bnarath/YouTube_Trending

After watching a couple of trending YouTube videos, we asked ourselves, what makes the videos popular !!! and what if we could predict the popularity !!! After all, we want to help the struggling YouTuber/influencer community by providing them with valuable insights on trending. At the same time, predicting popularity would help the advertising firms to identify the best videos to invest upon. Above all, we want to know, if there are any interesting insights underlying the trending patterns? This project is all about our journey towards finding these answers. Stay tuned !!!

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saminens/Predicting-Bankruptcy-of-firms

In class Kaggle competition on predicting bankruptcy of a firm

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Balaviknesh/Credit_Card-Fraud_Detection-AutoEncoders-XGB

Credit card Fraud Detection using AutoEncoders Neural network to encode complete dataset. Training the Genuine Transaction Data alone and create Anomaly Detecting Classification Model using the simple Logistic Regression Classifier and XGBoost to predict the Fraud transaction from the Encoded dataset.

Language: Jupyter Notebook - Size: 776 KB - Last synced at: about 2 years ago - Pushed at: almost 5 years ago - Stars: 2 - Forks: 0

heroorkrishna/Visibility_Climate

Building regression model

Size: 8.8 MB - Last synced at: about 2 years ago - Pushed at: about 5 years ago - Stars: 2 - Forks: 0

AbhishekSalian/Heart-disease-analysis-and-Prediction

Kaggle competition dataset anlaysis and prediction using machine learning algorithms

Language: Jupyter Notebook - Size: 300 KB - Last synced at: about 1 year ago - Pushed at: about 5 years ago - Stars: 2 - Forks: 0

abhilampard/Hospital-Readmission-Prediction-XGBoost

Prediction of a readmission for a patient based on the Electronic Health Records (EHR) data. This project was done as part of a timed challenge with a time limit of 3 hours to work on this dataset. So, it is just a preliminary model using XGBoost algorithm with some basic data exploration for data processing.

Language: R - Size: 4.45 MB - Last synced at: about 2 years ago - Pushed at: over 5 years ago - Stars: 2 - Forks: 1

ravising-h/The-Great-Data-Science-Challenge

A text analysis challenege on Hackerearth by Infosys where data was highly imbalanced.

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ChandraKiranSaladi/Earthquake_Prediction Fork of maneshreyash/Earthquake_Prediction

Predicting the time remaning for the next Earthquake. Kaggle Competition

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HarigovindV10/Credit-Card-Fraud-Detection

A credit card fraud detection algorithm.

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harsh306/fake_news_detection_deep_learning Fork of nguyenvo09/fake_news_detection_deep_learning

This repository is for Fake News Detection using Deep Learning models

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shubhampundhir/flight-fare-prediction

This is a end to end Data Science project where the task is to predict the Fare of the flights (Indian Only). Data is in the form of Excel spreadsheets, one is for training purpose and the other is for testing.

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DennisMuasyaWambua/car_blockchaininsurance_nextjs_animation

A Blockchain-AI powered car insurance system that incentivizes good driving by rewarding good drivers with lower monthly insurance premiums

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ajitonelsonn/chronic_disease_predictor

An advanced AI-powered tool for predicting chronic disease risks and providing personalized medical recommendations. The system utilizes machine learning to analyze patient data and generate risk assessments for various chronic conditions.

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zouzias/microgbt

microGBT is a minimalistic Gradient Boosting Trees implementation

Language: C++ - Size: 678 KB - Last synced at: 6 months ago - Pushed at: 6 months ago - Stars: 1 - Forks: 0

BhavyaMPatel/RetailRevolution

RetailRevolutioner, aims to provide a solution to the problem of accurately predicting consumer behavior in the retail industry. Our web application will analyze past sales data from clients to provide accurate predictions of which items will be the most popular in the coming month

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dhrupad17/CricMind-T20-World-Cup-Score-Predictor

The T20 World Cup Score Prediction project aims to predict the total runs scored by a team in a T20 cricket match using the XGBoost algorithm. XGBoost is a popular machine learning algorithm used for predictive modeling.

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abduallheid/Vitruvius-Construction-works-App

vitruvius is a wep app manage construction works

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Adidem23/RateEval

This is XgBoost based Model Which takes inputs from user and gives review from inputs

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brian-kipkoech-tanui/Regressionusecase

Regression

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HEMANGANI/Enrollment-Forecast

This project implements a machine learning forecast model using XGBoost to predict headcount based on historical data. The model preprocesses the data, trains on the training set, and generates predictions for the test set.

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Harsha-Vardhan-Tangudu/MACHINE-LEARNING-INTRUSION-DETECTION-SYSTEM

ML project based on intrusion detection system trained dataset

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minhtrang4078/Personal-Loan-Status-Prediction-App

Language: Jupyter Notebook - Size: 36.4 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 1 - Forks: 1

Princy02/Online-Auction-System

Auction Data Analysis and Predictive Modeling for Bid Feature Estimation

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facf00/Credit-Card---Churn-Rate

The credit churn data analysis aims to investigate the factors that contribute to customer attrition in a credit card company. The dataset used in this analysis contains information on customer demographics, credit card usage, and other relevant variables.

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yassmin1/machine_Learning_projects

Machine Learning Projects

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Major2000/CROPS-PRICE-TANZANIA

This project consists of a ML model that predicts the price trend of food crops in Tanzania especially Maize, Rice and Beans

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Vikash2009/Capstone-project-2-Bike-Sharing-Demand-Prediction

Capstone project 2-Bike sharing demand prediction. The goal of this project is to build a ML model that is able to predict the demand of rental bikes in the city of Seoul.

Language: Jupyter Notebook - Size: 3.46 MB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 1 - Forks: 0

Leangonplu/Ecommerce_Customer_Churn_Analysis_and_Prediction

Ecommerce Customer Churn Analysis and Prediction

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rammathala/Crop-And-fertilizer-recommendation

A website which predicts the suitable crop and fertilizer based on the soil parameters

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Mertdil/MachineLearning_model_with_Stock_Invesment

Machine Learning Model for Stock Investment

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tstran155/Multiclass-classification-of-breast-cancer-patients

In this notebook, I built gradient boosting classifier and neural network models to classify and predict the survival rate of patients with breast cancer.

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Sarthak-1408/Rain-Fall-Prediction

This repository represents the End to End Machine Learning Project (Rain Fall Prediction in Australia).

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rutujahingankar/nyc-taxi-trip-time-prediction

Predicts the total ride duration of taxi trips in New York City.

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jimschacko/Churn-Modelling-using-XGBoost

Churn Modelling using XGBoost

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MohamedWaelElsayed/Airbnb-Data-Science-Project

Complete data science airbnb project

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Simon-157/AI-final-project

A comprehensive data science project for analysing eCormmerce and online shops data for possibility to enegage customer retention to increase purchases. Trained and comprehensively evaluated machine learning models using different algorithms and tuning procedures.

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