Bloodwingv2/End-to-End-MLOps-Pipeline

End-to-End-MLOps-Diagnosis-Pipeline A hands-on MLOps project for disease diagnosis using machine learning — built with Python, Scikit-learn, XGBoost, FastAPI, Streamlit, MLflow, Docker, PostgreSQL, GitHub Actions, and Render. 🔗 Live Backend: https://mlops-1tdv.onrender.com

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HarishSinghRautela/Machine-Learning-Algorithm

this are a different 6 Algorithm with different type of data that is good for practice

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mcnaim0/Optimal_Engine_Crankshaft_Fatigue_Life_using_XGBoost

Optimizing engine crankshaft fatigue life using XGBoost

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Apaulgithub/Cardiovascular_Risk_Prediction

Machine learning project for cardiovascular risk prediction. The goal is to predict whether the patient has a 10-year risk of future coronary heart disease (CHD)

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JayanthSrinivas06/Fraudulent-Transactions-Detection

A machine learning web app to detect fraudulent financial transactions using Logistic Regression, Random Forest, and XGBoost.

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pashitox/tiktok_content_classifier

Clasificación de contenido en TikTok usando Machine Learning para detectar opiniones y reclamos a partir del texto transcrito.

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pashitox/Automata_taxi_tip_classifier

Modelo de aprendizaje automático para predecir si un pasajero de taxi en NYC dejará una propina igual o mayor al 20%.

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SunhengChea/NEXUS-AI

NEXUS-AI is a simple, reliable WhatsApp bot designed for seamless interaction. Fork and star the repository to contribute to this innovative project! 🐙🌟

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jinlow/forust

A lightweight gradient boosted decision tree package.

Language: Rust - Size: 13.4 MB - Last synced at: 18 days ago - Pushed at: 3 months ago - Stars: 74 - Forks: 7

Deshan-Senanayake/Bird-Range-Prediction

This is a lightweight web application that allows users to predict bird presence, location, and the best time to observe birds based on machine learning models trained on real birdwatching data from the Hambantota District.

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devspidr/stroke-prediction-using-ML

A machine learning project to predict stroke risk based on health data. Built using the XGBoost algorithm to achieve better accuracy and performance. Created as part of my learning journey into applying ML in healthcare domains.

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benedekrozemberczki/awesome-gradient-boosting-papers

A curated list of gradient boosting research papers with implementations.

Language: Python - Size: 1.48 MB - Last synced at: 16 days ago - Pushed at: over 1 year ago - Stars: 1,021 - Forks: 160

susanli2016/Machine-Learning-with-Python

Python code for common Machine Learning Algorithms

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aniass/Real-Estate-price-prediction

The real estate price prediction with linear regression models.

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100abhishek/Churn-Prediction-Model

Customer Churn Predictor is a machine learning web app that predicts whether a telecom customer is likely to leave the service. It analyzes customer details like tenure, contract type, monthly charges, and service usage using a trained XGBoost model. Users input data through a simple Gradio interface, and the app returns a real-time prediction.

Language: Python - Size: 253 KB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0

Vivek02Sharma/Student-Performance-Analysis-and-Prediction

Analyze and Predict student performance.

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ShubhamPaliwal03/TrafficTracer

A web application for botnet detection using Machine Learning - XGBoost, from the csv file containing network packet flows, captured using CICFlowMeter Tool.

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mdaltamashalam/Uber-Fare-Prediction-Models

Predicts the fare amount of Uber rides based on various factors such as pickup/drop-off coordinates, passenger count, and trip distance.

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RoushanKhalid/FUTURE_ML_01

This project develops a retail sales forecasting system using Prophet for automated time-series analysis and XGBoost for optimized predictions, enabling accurate demand forecasting.

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Tez1s/walmart_xgb_cv

Walmart Weekly Sales Forecasting Using XGB and Cross Validation 🚀

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chasedehan/BoostARoota

A fast xgboost feature selection algorithm

Language: Python - Size: 693 KB - Last synced at: 14 days ago - Pushed at: over 4 years ago - Stars: 222 - Forks: 38

MoinDalvs/Gradient_Boosting_Algorithms_From_Scratch

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

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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.

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Samhita-kolluri/DataUnveiledNYCAirbnb

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PAMPNA/Endocrine-Elegance-Classifying-Thyroid-Disorders-With-Precision

Early identification and treatment of thyroid disorders using predictive modeling. · Implemented Artificial Neural Networks (ANN), Support Vector Classifier(SVC), Random Forest, and XGBoost for risk prediction. · Developed a web application using ML Flask for user-friendly access to predictive models

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shashank-v-mishra/CP3_Cardiovascular-Risk-Prediction

It is a Capstone project. A model has been created to predict for the heart diseases. It can be very useful for the health sector as cardiovascular diseases are rapidly increasing. The record contains patients' information. It includes over 4,000 records and 15 attributes.

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FeziweMelvin/XGBoost-and-Random-Forest-for-Time-Series

This repository is for a project for using XGBoost and Random Forest Regressor to forecast time series

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philiptitus/Stroke-Prediction

This Project utilizes 3 Decision Tree Algorithms to make stroke Prediction models

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MaklonFR/PredictiveAnalytics-StudentsPerformance

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

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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

Language: JavaScript - Size: 2.31 MB - Last synced at: 29 days ago - Pushed at: 4 months ago - Stars: 1 - Forks: 1

prathamp25/SimpleHousePricePredictor_

A regression-based Machine Learning project predicting house prices using multiple models: Linear Regression, Random Forest, XGBoost, Gradient Boosting, SVR, and KNN. Includes feature engineering, visualization, and model comparison.

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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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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.

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beatass/Diamonds-price-analysis

The diamonds price prediction with linear regression models.

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itzdineshx/Mental-Health-EDA-Ensembling-models

This project focuses on predicting mental health status (Depression) using a dataset generated from a deep learning model trained on the Depression Survey.

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statbuster/sales-prediction

This project tackles the common real-life problem of sales prediction. You’ll work on the Big Mart Sales Prediction Challenge, learning regression techniques in R.

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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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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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himanshkr03/Comparative_Performance_on_FashionMNIST

This repository explores various machine learning and deep learning models for classifying images from the Fashion MNIST dataset. It includes data exploration, model training, evaluation, and visualization techniques to gain insights into the classification task.

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adithi741/bank-customer-churn-prediction_using_XGBoost_alg

"A machine learning project to predict bank customer churn using the XGBoost algorithm. Includes feature engineering, model training, and results visualization."

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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: 6 months ago - Pushed at: 6 months ago - Stars: 21 - Forks: 7

Yash-3-bit/Solar-Irradiance-Prediction

Solar irradiance prediction involves forecasting the amount of solar energy reaching a given area over a specific time period. This is critical for optimizing solar power generation, energy storage, and grid management. Here's an overview of the key concepts, methods, and tools involved:

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GitData-GA/h5n1

The study focuses on modeling and predicting H5N1 bird flu outbreaks in the United States at the county level, utilizing diverse statistical techniques and machine learning models.

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Saket046/Red-wine-quality-predictor

Red wine quality prediction machine learning model.

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Vimal007Vimal/Malicious-URL-Detection

Our project employs machine learning to pinpoint phishing URLs with 97.4% accuracy, leveraging HTTPS and website traffic as critical indicators. Insights into features like AnchorURL enhance cybersecurity strategies, showcasing the power of AI in combating online threats.

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zouzias/microgbt

microGBT is a minimalistic Gradient Boosting Trees implementation

Language: C++ - Size: 678 KB - Last synced at: 8 months ago - Pushed at: 8 months ago - Stars: 1 - Forks: 0

mieskolainen/icenet

D<ee>p Learning [dev library]

Language: Python - Size: 27.1 MB - Last synced at: 8 months ago - Pushed at: 8 months ago - Stars: 3 - Forks: 6

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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RudreshVeerkhare/CustomXGBoost

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

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leonardodepaula/xgbimputer

Extreme Gradient Boost imputer for Machine Learning.

Language: Python - Size: 120 KB - Last synced at: 25 days ago - Pushed at: over 3 years ago - Stars: 8 - Forks: 1

RamEppala/imbalanceddatasetproject

Machine Learning Project on Imbalanced Data in R

Language: R - Size: 5.69 MB - Last synced at: about 2 months ago - Pushed at: over 7 years ago - Stars: 3 - Forks: 3

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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Dan-A2/Diabetes-Analysis

Diabetes Health Indicator Dataset analysis with R

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dileepkorade/Machine-Learning_Projects

Projects based on Machine Leaning

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VishalSinhaRoy/Fraud_Detection-Online_Transaction---ML

This study involves employing machine learning models and anomaly detection approaches, such as over- and under-sampling, to detect fraud in online transactions.

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rosaaldama278/ml-customer-financial-products

This repository presents a comprehensive analysis of bank customer financial product ownership using advanced machine learning techniques. The project leverages a rich dataset containing demographic information, product ownership details, and other relevant attributes such as country of residence, age, and gross income.

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MuafiraThasni/Electricity-Demand-Forecasting

Repository for Electricity demand forecasting project, containing notebooks for EDA and Modeling, and the data files.

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rudrajikadra/Parkinsons-Disease-Detection-ML-Project-with-XGBClassifier

In this project, I have created a Machine Learning model using XGBClassifier to Detect Parkinsons Disease with eXtreme Gradient Boosting (XGBoost).

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MohanSistla/Learning-to-rank-ML-Model

Learning to rank is an algorithmic technique employing machine learning models to solve ranking problems

Language: Python - Size: 7.46 MB - Last synced at: 12 months ago - Pushed at: over 3 years ago - Stars: 1 - Forks: 0

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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Priyanshu-21/Crop-Prediction

Predicting the best suitable crop based on various parameters. The model is based on Random Forest Algorithm

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suraj5424/Movements-from-Skeleton-Data

Predict future movements from skeleton data. Utilize XGBoost classifier on time series of 3D skeleton data for tasks like fall detection or gesture recognition. Preprocess, train, evaluate, and predict for submission.

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shahidulislam-cse/Machine-Learning-with-XGboost

XGBoost (Extreme Gradient Boosting) is a highly efficient and accurate machine learning algorithm based on gradient boosting, excelling in structured data tasks. It includes features like regularization, handling missing values, and parallel processing. Widely used in competitions and industry, it supports multiple programming languages.

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abduallheid/Vitruvius-Construction-works-App

vitruvius is a wep app manage construction works

Language: JavaScript - Size: 37.6 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 1 - Forks: 1

haseebshaik00/Detecting-Heart-Diseases

Comparative Analysis for Various Classification Machine Learning Algorithms for Detecting Heart Diseases

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dakshtrehan/Parkinson-Disease-Detector

Supervised Learning

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Bernardbyy/SpotifyMusicClassifier

Spotify Music Classifier with Machine Learning Using Spotify API

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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: 3 months ago - Pushed at: over 3 years ago - Stars: 2 - Forks: 3

naiborhujosua/NYC-Trip-Duration

This is a comprehensive Exploratory Data Analysis for the New York City Taxi Trip Duration competition with Python and Data Visualization libraries such as matplotlib and seaborn to predict the duration of taxi rides in NYC based on features like trip coordinates or pickup date and time.

Size: 435 KB - Last synced at: about 1 year ago - Pushed at: almost 4 years ago - Stars: 0 - Forks: 0

PrasunDatta/Detection-of-Covid-19-from-Chest-Radiographs

This research work serves the purpose of detecting covid-19 from chest x-ray images. During the pandemic, we have conducted this research realizing the gravity of it during those time.

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METALXRAY/House-Price-Prediction-using-Machine-Learning-with-Python

Prediciting the Prices of House using the Boston House Price Dataset by applying the XGBoost Regressor Model

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VctrEman/Optimization-with-Deep-Learning

Language: Jupyter Notebook - Size: 304 KB - Last synced at: about 1 year ago - Pushed at: almost 4 years ago - Stars: 0 - Forks: 0

kowsalya0092/currency-exchange-prediction

This project leverages machine learning to forecast currency exchange rates to help optimize expenses in the face of fluctuating currencies.

Language: Jupyter Notebook - Size: 196 KB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0

VictorUmunna/Titanic_Challenge

A classification project to determine if a passenger survived the Titanic crash or not.

Language: Jupyter Notebook - Size: 112 KB - Last synced at: about 1 year ago - Pushed at: over 4 years ago - Stars: 0 - Forks: 0

VictorUmunna/Loan_Prediction

A classification project to determine the eligibility of getting a loan after filling an online form

Language: Jupyter Notebook - Size: 468 KB - Last synced at: about 1 year ago - Pushed at: over 4 years ago - Stars: 0 - Forks: 0

yash-gajjjar/Bangalore-Housing-Price-Prediction-ML

Used Linear Regression, Decision Tree, Random Forest and XGBoost, AdaBoost, LightGBM and CatBoost ML Algorithm to Predict Bangalore housing price.

Language: Jupyter Notebook - Size: 608 KB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0

thuvarahan97/DataStorm1.0_TeamFixzels 📦

Data Storm 1.0 - Business Problem - Team Fixzels

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eswar3/Zillow-prediction-models

Machine Learning Project using Kaggle dataset

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shouryasimha/NLP

I have started getting quite interesting in the concept of Natural Language Processing and tried to implement and understand this concept from a blog i read from towardsdatascience.com

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yash-gajjjar/Energy-Consumption-Time-Series-XGBoost-ML

Used XGBoost Gradient Boosting Decision Tree Supervised ML Algorithm

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AnFrBo/order_returns_prediction

Prediction of Order Returns of an Online Clothing Retailer (Real-World Data) With XGBoost and Random Forest

Language: R - Size: 5.66 MB - Last synced at: 2 months ago - Pushed at: over 4 years ago - Stars: 1 - Forks: 1

Mayuur25/Amazon-Revirew-NLP-ML-Project

In this project i am trying to use NLP, ML concepts on Amazon reviews using various ML based model like XGBoost, Decision tree classifier and random forest

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harmonicfunc/LogicalRhythm2k23

Logical Rhythm is annual Machine learning competition hosted on Kaggle under Avishkar (Official Technical Fest of MNNIT)

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contactrameezraja/Machine-Learning-with-Python-projects

Python code for Machine Learning Algorithms

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SK7here/Extreme-gradient-boosting-parameter-tuning

Parameters of extreme gradient boosting model are fine tuned to achieve better accuracy

Language: Python - Size: 2.13 MB - Last synced at: over 1 year ago - Pushed at: about 6 years ago - Stars: 1 - Forks: 0

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: over 1 year ago - Pushed at: over 1 year ago - Stars: 19 - Forks: 10

abhi227070/Salary-Price-Prediction

Salary Prediction API using Flask predicts salaries for freshers joining organizations based on factors like past experience, company switches, courses completed, and academic marks. This Flask-based API allows users to input their details and receive a salary prediction. With no user interface, it's designed for integration into other applications

Language: Python - Size: 273 KB - Last synced at: about 2 months ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

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: about 2 years ago - Stars: 8 - Forks: 1

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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Thangam-11/Final-Project

The Food Price Estimation project focuses on providing estimates of food prices to capture local price fluctuations in regions where people are vulnerable to localized price surges. The project utilizes a machine-learning algorithm designed to predict ongoing subnational price surveys, demonstrating accuracy comparable to direct price measurements.

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dorianDraper/Boosting-Algorithms

Applying boosting techniques such as GradientBoostingClassifier, GradientBoostingRegressor (eXtreme Gradient Boosting (XGBClassifier and XGBRegressor functions). This repo contains class examples and the project.

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AbhishekSalian/Heart-disease-analysis-and-Prediction

Kaggle competition dataset anlaysis and prediction using machine learning algorithms

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danieljosephraj/LGMVIP-DataScience

LetsGrowMore DataScience Internship: During this Internship, I have worked on project related to Data Analytics field in which LSTM, Decision Tree, Random Forest and XGboost have been used.

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Talieh-Sh/Bank_Churn_Project

Project uses ML models (XGBoost, Regression, RandomForest, Neural Networks) to predict bank customer churn. XGBoost led with 86.73% accuracy. Utilized Tableau for visualization, hosted online via Docker, Neon, Flask.

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josecruzado21/credit_card_fraud_detection

This project is about detecting fraudulent credit card transactions. The dataset tends to be highly imbalanced, with less than 0.2% of the observations labelled as fraudulent. To address this issue we have to take into account the bank's objective (maximizing precision or recall) and restrictions. The performance and efficiency of many classification algorithms (Logistic Regression, XGBoost, Random Forests) were tested and compared.

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Sarthak-Mohapatra/US-Airlines-Tweets-Sentiment-Analysis

Classifying a tweet as positive, neutral, or negative sentiment using Natural Language Processing (CBOW approaches) and Traditional Machine Learning Algorithms.

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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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Adidem23/RateEval

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

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Cintia0528/Data_Science-Supervised_Machine_Learning_Classification_Housing

The projects aim is to find the to best ML algorithm evaluated on its efficiency in predicting whether homes should be classified as expensive or not expensive.

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