This project focuses on predicting welding quality based on time series data of electrical current and voltage measurements. The analysis employs various machine learning techniques to extract meaningful features from welding process data, identify patterns through clustering, and build predictive models for quality classification.

In this mini-project, we can predict milk quality by color, pH, fat & etc .I used KNN algorithm to classify.

This repository contains my work on Oasis Info byte’s data analytics one month internship program.

A Matlab implementation of a multi-objective optimization algorithm called GADMS for key quality characteristic selection (feature selection).

A machine learning classification approach for risk detection in battery cell manufacturing

Quantization quality analyzer — pure-Python GGUF/safetensors parser, layerwise sensitivity, quality prediction. Zero deps.

This project is to predict the quality of wine based on features like alcohol content and density, using a publically available dataset. The target variable of "quality" is a subjective measure of the wine's quality based on expert tasters. I am using pandas, numpy, torch and matplotlib in python.

This repository contains the implementation for our research on out-of-distribution (OOD) detection in gas metal arc welding (GMAW) quality prediction. Our work addresses critical challenges in dynamic manufacturing environments where process parameters frequently change, causing distribution shifts that degrade model performance.

AI-powered VoIP call quality prediction and anomaly detection with ML and ITU-T G.107 E-model

This is my coursework for the fourth semester of the first year at KPI, in which I implemented a system for predicting water quality using various machine learning models

This project focuses on visualizations for predicting weld quality based on time-series data of electrical current and voltage measurements. The analysis employs various machine learning techniques to extract meaningful features from welding process data, identify patterns through clustering, and build predictive models.

PRISM — AI-driven batch-level predictive modelling & energy pattern intelligence for pharmaceutical manufacturing. Built for the National AI/ML Hackathon by AVEVA.