Open-Source Kaggle Solution: Predicting Multi-Market Commodity Prices with Tree Models

An open-source, Kaggle‑ranked solution for the Mitsui Commodity Prediction Challenge details data preprocessing, feature engineering, and multiple tree‑based modeling strategies—including multi‑target, single‑target, and price‑difference models—with code, evaluation metrics, and suggestions for further improvements.

CatBoostCommodityFeatureEngineering

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Open-Source Kaggle Solution: Predicting Multi-Market Commodity Prices with Tree Models

DataFunTalk

Aug 3, 2022 · Artificial Intelligence

Building a Complete Machine Learning Application with OpenMLDB and OneFlow: JD High‑Potential User Purchase Intent Prediction

This tutorial demonstrates how to use OpenMLDB together with OneFlow to build an end‑to‑end machine‑learning pipeline for predicting high‑potential JD users' purchase intent, covering environment setup, data loading, SQL table creation, offline feature extraction, DeepFM model training, model serving, online feature extraction, deployment, and real‑time inference.

DockerFeatureEngineeringModelServing

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Building a Complete Machine Learning Application with OpenMLDB and OneFlow: JD High‑Potential User Purchase Intent Prediction

DataFunTalk

Mar 8, 2022 · Databases

OpenMLDB 0.4.0 Full-Process Features and Quick‑Start Guide for Building End‑to‑End Online AI Applications

This article introduces the new full‑process features of OpenMLDB 0.4.0, explains its unified online/offline storage, high‑availability task management, and end‑to‑end AI workflow, and provides step‑by‑step instructions for quickly deploying both single‑node and cluster versions to run a complete online AI application.

AIWorkflowDistributedSystemsFeatureEngineering

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OpenMLDB 0.4.0 Full-Process Features and Quick‑Start Guide for Building End‑to‑End Online AI Applications