There are 3 repositories under xgboost-python topic.
Hospital admission data was analyzed to accurately predict the patient’s Length of Stay at the time of admit so that the hospitals can optimize resources and function better.
Implement common statistical machine learning algorithms with raw Numpy.
Machine-Learning: eXtreme Gradient-Boosting Algorithm Stress Testing
Introduction to XGBoost with an Implementation in an iOS Application
This project is a part of research on Breast Cancer Diagnosis with Machine Learning algorithm using data-driven approaches. The final outcomes of the research were later published at an IEEE Conference and added to IEEE Xplore Digital Library.
Angular 8 application for course project using AWS AND ML features
Credit Card Fraud Detection using Machine Learning
XTune: A custom python wrapper for XGBoost and LightGBM with numerous utility functions to prevent silly gotchas and save time!
Southern Data Science Conference Attempt 2020
This project is a part of research on Breast Cancer Diagnosis with a Machine Learning algorithm using data-driven approaches. The final outcomes of the research were later published at an IEEE Conference and added to IEEE Xplore Digital Library.
Kaggle Competition (Encoding categorical variables)
build a model that accurately detect the presence of Parkinson’s disease in an individual.
Built Random Forest and GBDT using XGBOOST model on Amazon fine food review dataset
Self-taught applications of Machine Learning Model XGBoost for COMP4650
Walmart Sales Forecast Solution
Jupyter-Lab based setup for data science (Conda, TF2, XGBoost GPU)
Predictions and Analysis of Customer Churn for Telecoms Company with Plotly Dash Application.
Three levels of DataWorkshop Matrix Transformation
Consumer Spending Analytics
Predicting heart failure by cardiovascular diseases (CVD).
A comparative breakdown of traditional econometric timeseries models vs. more modern ML methods for predicting a retail firm's sales over a short to medium horizon
ML projects coded during Matrix 2 by DataWorkshop - car prices prediction
An XGBoost model in Python that classifies if a customer will cancel his/her hotel booking or not. I also use counterfactuals guided by prototypes from the Alibi package to explore the minimum changes needed to flip a prediction from canceled to not canceled and vice versa.
Demographic Prediction using user browser history
This is React + Django app which helps users to predict the right resell price for the car and It will interpret the output
This repository is about demonstrating XgBoost's Gradient boosting capability with Boston Housing Dataset.
Develop a supervised model which can predict customer segment (Low, Medium, high) in Python based on XGBClassifier
☕️Customer segmentation to identify the parts of the population that best describe the core customer base of the company; Predict which individuals are the most likely to respond to the company's mail campaigns.
TCD ML Comp. 2019/20 - Income Prediction (Ind.)
Demonstrating how to build an XGBoost model and deploy it to Algorithmia, from a Jupyter notebook
Exploratory Data Analysis and Prediction on Pima Indians Diabetes Dataset