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Introduction to XGBoost with an Implementation in an iOS Application

Home Page: https://heartbeat.fritz.ai/introduction-to-xgboost-with-an-implementation-in-an-ios-application-cdfaa8f9930b

Swift 97.13% Python 2.87%
xgboost xgboost-algorithm xgboost-python coremltools ios-app ios-swift swift python machine-learning ensemble-machine-learning

xgboost_student_performance's Introduction

Introduction to XGBoost with an Implementation on an iOS Application

Train and deploy XGBoost models using coremltools and build an on-device experience using Swift and Core ML

Final Results

All the python packages required are in the ./training/requirements.txt file, you just need to install them by running the following command in your shell:

pip install -r requirements.txt

Train the model

MacOS, Linux:

python app.py

About me

Omar MHAIMDAT – Linkedin[email protected]

Distributed under the MIT license. See LICENSE for more information.

Look at the rest of my repos

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