Complete data architecture and machine learning project for industrial cost analysis. Includes a modern ETL pipeline (Bronze-Silver-Gold), validations with Great Expectations, Prefect orchestration, in-depth EDA, predictive models (Random Forest and Gradient Boosting), and deployment via Streamlit.

This repo is a fork of https://github.com/grafana/grafana as used by Empolis Information Management GmbH as part of Empolis Service Express Industrial Analytics.

PSistema de monitoreo predictivo para enfriadores de ácido sulfúrico (CAP-3), basado en ingeniería térmica, análisis de ensuciamiento, evaluación de criticidad y machine learning supervisado.

Machine learning pipeline for predicting industrial gold recovery, optimizing process efficiency using sMAPE and ensemble regression models.

End-to-end predictive maintenance project on the AI4I 2020 dataset. Includes feature engineering, calibrated logistic regression and random forest pipelines, with attention to class imbalance and operating-point evaluation (PR-AUC, recall @ 90% precision).

Exactspace Data Science Take-Home Assignment: Industrial sensor analytics, clustering, anomaly detection, forecasting, and a retrieval-augmented generation (RAG) LLM prototype – by Gunal D (BTech CSE, Bangalore).

Sistema digital predictivo para el monitoreo térmico de intercambiadores EP-101 en Planta de Ácido (Chuquicamata), basado en Python, Streamlit y analítica avanzada para mantenimiento predictivo.

中国石油大学（华东）工程概论课程作业-对计算机领域复杂工程问题进行案例分析-三维计算机图形软件的设计与开发

This project implements an Artificial Neural Network (ANN) to predict the net hourly electrical energy output (PE) of a combined cycle power plant.

📊 Analyze machine data through cleaning, clustering, anomaly detection, and forecasting to improve operational efficiency and insights.