This is a script designed to deploy a ML Model via Client-Side FastAPI !

Еffective method of working with large MLM structures

bubble_insp_ver0.1 is a lightweight ML pipeline for detecting, counting, and tracking bubbles in reactor flow—built for quality control in advanced manufacturing. Using YOLOv8 segmentation, it supports real-time video analysis, size measurement, and deployment on edge devices like the Raspberry Pi 5, Specifically built for minimal hardware.

Flight Price Prediction EDA, Data Pre-Processing and ML Model Building

ML

Cardiovascular_Risk_prediction : The dataset is from an ongoing cardiovascular study on residents of the town of Framingham, Massachusetts. The classification goal is to predict whether the patient has a 10-year risk of future coronary heart disease (CHD).

An automated, collaborative ethical bias auditing platform for ML models. Demo:https://youtu.be/8mE_vLP9TYc

ML model application

Created a Model that estimates Flight Prices to help users look for best prices when booking flight tickets, Engineered features from the Departure Time, Date of Journey, to quantify the data and make it more understandable. Optimized multiple Regression models using GridsearchCV to reach the best model.

Analytics Vidya (Loan Prediction)