Predicting Water Quality Using Intel AI Analytics Toolkit
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.
Speaker(s)
Jiacheng Wan - University of Science and Technology of China/Academic Master
Jiacheng Wan received an undergraduate degree from the School of Computer Science, University of Science and Technology of China. He received the third prize in the Compilation System Design Competition in the second section of the Computer System Ability Competition.
Ce Sun - University of Science and Technology of China/Academic Master
Ce Sun is a 2023 graduate student of the School of Computer Science, University of Science and Technology of China. He has won the 2021 National third prize in the finals of the college student computer system ability competition, and his current research direction is in a unified programming framework for heterogeneous computing Frame design and realization.
