There are 1 repository under xgb topic.
A Machine Learning API with native redis caching and export + import using S3. Analyze entire datasets using an API for building, training, testing, analyzing, extracting, importing, and archiving. This repository can run from a docker container or from the repository.
This is a Machine Learning web app developed using Python and StreamLit. Uses algorithms like Logistic Regression, KNN, SVM, Random Forest, Gradient Boosting, and XGBoost to build powerful and accurate models to predict the status of the user (High Risk / Low Risk) with respect to Heart Attack and Breast Cancer.
Data and Code to reproduce results for my talk at Paris: R in Insurance 2017 Conference
Gocaudices is a dwmblocks alternative written in GO in less than 100 SLOC using xgb.
Kaggle Bosch Production Line Performance, NO.74/top 6% (post competition analysis) 生產線分析、前 6 % ( 賽後分析 )
Utilizing AutoXGB for Credit Card Financial Fraud Detection
A dashboard that supports fleet managers and decision makers to gain insights into their automotive fleets and optimize them
Microbial Phenotype Prediction, successor to PICA, implemented with Python 3.7 and scikit-learn
Code used in Kaggle's Santander Product Recommendation competition.
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.
A python 2 container runtime for processing data science tasks and workloads (used by https://github.com/jay-johnson/sci-pype for distributed analysis)
Kaggle Property Market competition solution
PSO Fuzzy XGBoost Classifier Boosted with Neural Gas Features on EEG Signals in Emotion Recognition
comparison of different machine learning models such as GB, XGB and NN to see which performs better at real time SYN flood detection
The main of this solution is to identify the churn customers and to find important features for identifying churn customer.
This is the Classification supervised learning model used for predicting employee will get promotion or not
Consumer Spending Analytics
This project is a part of Machine Learning Class for Data Science Master Program from Simplilearn
building a model to predict whether a food establishment passed inspection or not
MachineHack Hackathon
Synthetic Financial Datasets For Fraud Detection
End to End Accident Prediction App with Hotspot Analysis
NIRF Rank Predictor: Web scraping, OCR, Model training using XGBoost, feature extraction using SHAP and permutation analysis.
🥇 1st Place & Best Project Overall Stats Under the Stars 8 Hackathon (#SUS8) Organized by
churnxgb :chart_with_downwards_trend::rocket::grinning: : Customer Churn Predictions # BQML # XGBoost Classifier
Predicting online news popularity using classical and ensemble ML models on Spark
Predicting future sales for Walmart stores using historical data, calendar features, and advanced regression models. This project covers data preprocessing, feature engineering (lag values & time-based), model training using Linear Regression and XGBoost, and visual analysis with rolling averages and seasonal decomposition.