Prediction of Fresh Water Quality with XGBoost and Modin: Developer Spotlight

Predicting fresh water quality is important for protecting human health, environmental health, economic development, and effective water management. Arpan Mondal, in his blog, proposed a solution for predicting the quality of fresh water using Intel® Distribution of Modin*, XGBoost optimizations from Intel, and Intel® oneAPI Data Analytics Library:

• Intel Distribution of Modin - to analyze and preprocess the dataset
• XGBoost optimizations from Intel - to create the classification model
• daal4py from Intel oneAPI Data Analytics Library (oneDAL) - to perform inference on the XGBoost model.

The blog explains the various steps involved in the project:

1. Setup the environment
2. Exploratory Data Analysis and Data Preprocessing
3. Model Training
4. Implement the web app using docker
5. Model Testing

Read more about the project on Medium and GitHub.

Learn more about XGBoost Optimizations from Intel and Intel Distribution of Modin

XGBoost optimizations from Intel: XGBoost with Intel optimizations will automatically accelerate performance on Intel hardware without any code changes. Additionally, Intel developed a fast tree-inference capability in the daal4py library to speed up gradient-boosting inference without sacrificing accuracy.

Intel Distribution of Modin: Modin is a drop-in replacement for the extensively used Python library Pandas. Intel® Distribution of Modin is a performant, parallel, distributed data frame system that accelerates Pandas using a fully compatible API. This adds optimizations to accelerate processing on Intel® hardware further.

Download XGBoost optimizations from Intel and Intel Distribution of Modin as part of the AI Tools.

What’s Next?

We encourage you to check out and incorporate Intel’s other AI/ML Framework optimizations and end-to-end portfolio of tools into your AI workflow and learn about the unified, open, standards-based oneAPI programming model that forms the foundation of Intel’s AI Software Portfolio to help you prepare, build, deploy, and scale your AI solutions.

About the Author:

Arpan Mondal is pursuing his bachelor's in computer science at Sister Nivedita University. He is the Chief Executive Officer of Fund Tokens DAO (FTDAO), leading the decentralized investments for renewable energy, net-zero projects, electric vehicles, and environmental, social & governance (ESG) initiatives.