Kaggle Kernels that use AutoML and Intel® Extension for Scikit-learn*

The following Kaggle kernels show how to patch autoML framewokrs with Intel® Extension for Scikit-learn*.

TPS stands for Tabular Playground Series, which is a series of beginner-friendly Kaggle competitions.

Kernel

Goal

AutoML MultiClass Classification (Gradient Boosting, Random Forest, kNN) using AutoGluon with Intel® Extension for Scikit-learn*

Data: [TPS Jun 2021] Synthetic eCommerce data

Predict the category of an eCommerce product

AutoML Binary Classification (Gradient Boosting, Random Forest, kNN) using AutoGluon with Intel® Extension for Scikit-learn*

Data: Titanic datset

Predict whether a passenger survivies

AutoML Binary Classification (Gradient Boosting, Random Forest) using AutoGluon with Intel® Extension for Scikit-learn*

Data: [TPS Oct 2021] Synthetic molecular response data

Predict the biological response of molecules given various chemical properties

AutoML Binary Classification (Gradient Boosting, Random Forest, kNN) using EvalML and AutoGluon with Intel® Extension for Scikit-learn*

Data: [TPS Nov 2021] Synthetic spam emails data

Identify spam emails via features extraced from the email