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.

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).

Predictive maintenance system that analyzes industrial sensor data to estimate machine failure risk and visualize equipment health through a FastAPI and React dashboard.

UniversityHack 2024 challenge solution focused on lot-level industrial analytics and predictive modeling.

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

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

Chairperson Award — 1st Position · Python + HTML/CSS · Automated PI/DCS data extraction, real-time & historical trend analysis, equipment health monitoring & one-click DSM report generation · Zero manual DCS entry · Jindal Power Limited

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

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.

End-to-end industrial analytics solution for energy optimization in manufacturing | ML forecasting, inefficiency detection, and cost reduction insights with Power BI

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).

Playing around with industrial energy data to find insights on power consumption and CO2 emissions.

Chairperson Award — 1st Position · AppSheet + Google Sheets app digitising SOPs, manuals, Signal Flow Diagrams & hardware schemes with digital checklists, calibration records & one-click HOD email approval workflow · Jindal Power Limited

Enterprise-style forecasting and operational intelligence platform for industrial energy analytics, predictive operations, and energy demand forecasting.

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