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.
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Updated
Oct 23, 2023 - Jupyter Notebook
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.
Introduction to XGBoost with an Implementation in an iOS Application
Machine-Learning: eXtreme Gradient-Boosting Algorithm Stress Testing
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.
Credit Card Fraud Detection using Machine Learning
Angular 8 application for course project using AWS AND ML features
XTune: A custom python wrapper for XGBoost and LightGBM with numerous utility functions to prevent silly gotchas and save time!
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.
XGBoost is an open-source machine learning library that provides efficient and scalable implementations of gradient boosting algorithms. It is known for its speed, performance, and accuracy, making it one of the most popular and widely-used machine learning libraries in the data science community.
Southern Data Science Conference Attempt 2020
Self-taught applications of Machine Learning Model XGBoost for COMP4650
Kaggle Competition (Encoding categorical variables)
Jupyter-Lab based setup for data science (Conda, TF2, XGBoost GPU)
build a model that accurately detect the presence of Parkinson’s disease in an individual.
Walmart Sales Forecast Solution
Built Random Forest and GBDT using XGBOOST model on Amazon fine food review dataset
Predictions and Analysis of Customer Churn for Telecoms Company with Plotly Dash Application.
Exploratory Data Analysis and Prediction on Pima Indians Diabetes Dataset
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