They will share how the team leveraged multiple components from the oneAPI AI Analytics Toolkit and API-based programming library to solve the problem of “predicting water quality” in the oneAPI Hackathon AI track. Leverage up to 6 models (lightgbm, xgboost, catboost, etc.) in their final solution and explore multiple optimization options to accelerate inference on Intel platforms, including using daal4py, oneDAL (C++). This complete solution includes data preprocessing, model classifier and fitting, standard model and D4P model conversion, and supports Python and C++ languages for final inference. They also performed some preliminary performance evaluations of different optimization options and approaches, and shared some preliminary findings while investigating solutions to the challenges.